Innovative and entrepreneurial activity in the public sector : the changing face of public sector institutions

This paper investigates the elements which support innovative and entrepreneurial activity in New Zealand’s state owned enterprises (SOEs). An inductive case study design, involving interview data, textual analysis, and observation, was applied to three SOEs. Findings reveal that those aspects typically associated with entrepreneurship, such as innovation, risk acceptance, pro-activeness and growth, are often supported by a number of unexpected elements within the public sector. These elements include culture, branding, operational excellence, cost efficiency, and knowledge transfer. The implications are twofold. First, that innovative and entrepreneurial activity in the public sector can go beyond policy-making, with SOEs representing an important policy decision and sector of the New Zealand Government. And second, that the impact of several SOEs on international markets suggests competition on the global stage will increasingly come from both public and private sector organizations.

Systems-based accident analysis in the led outdoor activity domain : application and evaluation of a risk management framework

Safety-compromising accidents occur regularly in the led outdoor activity domain. Formal accident analysis is an accepted means of understanding such events and improving safety. Despite this, there remains no universally accepted framework for collecting and analysing accident data in the led outdoor activity domain. This article presents an application of Rasmussen's risk management framework to the analysis of the Lyme Bay sea canoeing incident. This involved the development of an Accimap, the outputs of which were used to evaluate seven predictions made by the framework. The Accimap output was also compared to an analysis using an existing model from the led outdoor activity domain. In conclusion, the Accimap output was found to be more comprehensive and supported all seven of the risk management framework's predictions, suggesting that it shows promise as a theoretically underpinned approach for analysing, and learning from, accidents in the led outdoor activity domain.

Expert elicitation and its interface with technology : a review with a view to designing Elicitator

Expert knowledge is valuable in many modelling endeavours, particularly where data is not extensive or sufficiently robust. In Bayesian statistics, expert opinion may be formulated as informative priors, to provide an honest reflection of the current state of knowledge, before updating this with new information. Technology is increasingly being exploited to help support the process of eliciting such information. This paper reviews the benefits that have been gained from utilizing technology in this way. These benefits can be structured within a six-step elicitation design framework proposed recently (Low Choy et al., 2009). We assume that the purpose of elicitation is to formulate a Bayesian statistical prior, either to provide a standalone expert-defined model, or for updating new data within a Bayesian analysis. We also assume that the model has been pre-specified before selecting the software. In this case, technology has the most to offer to: targeting what experts know (E2), eliciting and encoding expert opinions (E4), whilst enhancing accuracy (E5), and providing an effective and efficient protocol (E6). Benefits include: -providing an environment with familiar nuances (to make the expert comfortable) where experts can explore their knowledge from various perspectives (E2); -automating tedious or repetitive tasks, thereby minimizing calculation errors, as well as encouraging interaction between elicitors and experts (E5); -cognitive gains by educating users, enabling instant feedback (E2, E4-E5), and providing alternative methods of communicating assessments and feedback information, since experts think and learn differently; and -ensuring a repeatable and transparent protocol is used (E6).

Concurrent and prospective associations between physical activity, walking and mental health in older women

Background Leisure-time physical activity (LTPA) shows promise for reducing the risk of poor mental health in later life, although gender- and age-specific research is required to clarify this association. This study examined the concurrent and prospective relationships between both LTPA and walking with mental health in older women. Methods Community-dwelling women aged 73–78 years completed mailed surveys in 1999, 2002 and 2005 for the Australian Longitudinal Study on Women's Health. Respondents reported their weekly minutes of walking, moderate LTPA and vigorous LTPA. Mental health was defined as the number of depression and anxiety symptoms, as assessed with the Goldberg Anxiety and Depression Scale (GADS). Multivariable linear mixed models, adjusted for socio-demographic and health-related variables, were used to examine associations between five levels of LTPA (none, very low, low, intermediate and high) and GADS scores. For women who reported walking as their only LTPA, associations between walking and GADS scores were also examined. Women who reported depression or anxiety in 1999 were excluded, resulting in data from 6653 women being included in these analyses. Results Inverse dose–response associations were observed between both LTPA and walking with GADS scores in concurrent and prospective models (p<0.001). Even low levels of LTPA and walking were associated with lowered scores. The lowest scores were observed in women reporting high levels of LTPA or walking. Conclusion The results support an inverse dose–response association between both LTPA and walking with mental health, over 3 years in older women without depression or anxiety.