Tracking brand positioning for an emerging destination: 2003 to 2015

Few published studies have monitored destination brand image over time. This temporal aspect is an important gap in the literature, given consensus around the role perceptions play in consumers’ decision making, and the ensuing emphasis on imagery in destination branding collateral. Whereas most destination image studies have been a snapshot of perceptions at one point in time, this paper presents findings from a survey implemented four times between 2003 and 2015. Brand image is the core construct in modelling destination branding performance, which has emerged as a relatively new field of research in the past decade. Using the consumer-based brand equity (CBBE) hierarchy, the project has benchmarked and monitored destination brand salience, image and resonance for an emerging regional destination, relative to key competitors, in the domestic Australian market; and the survey instrument has been demonstrated to be reliable in the context of short break holidays by car. What is particularly interesting to date is there has been relatively little change in the market positions of the five destinations, in spite of over a decade of marketing communications by the regional tourism organisations and their stakeholders, and more recently the mass of user-generated travel content on social media. The project didn’t analyse the actual marketing communications for each of the DMOs. Therefore an important implication is that irrespective of the level of marketing undertaken the DMOs seem to have had little control over the perceptions held in their largest market during this time period. Therefore it must be recognised any improvement in perceptions will likely take a long period of time, and so branding needs to be underpinned by a philosophy of a long term financial investment as well as commitment to a consistency of message over time; which given the politics of DMO decision making represents a considerable challenge.

Modelling, calibrating, and validating car following and lane changing behaviour

Car following (CF) and lane changing (LC) are two primary driving tasks observed in traffic flow, and are thus vital components of traffic flow theories, traffic operation and control. Over the past decades a large number of CF models have been developed in an attempt to describe CF behaviour under a wide range of traffic conditions. Although CF has been widely studied for many years, LC did not receive much attention until recently. Over the last decade, researchers have slowly but surely realized the critical role that LC plays in traffic operations and traffic safety; this realization has motivated significant attempts to model LC decision-making and its impact on traffic. Despite notable progresses in modelling CF and LC, our knowledge on these two important issues remains incomplete because of issues related to data, model calibration and validation, human factors, just to name a few. Thus, this special issue will focus on latest developments in modelling, calibrating, and validating two primary vehicular interactions observed in traffic flow: CF and LC.

Biological and environmental determinants

This chapter describes biological and environmental determinants of the health of Australians, providing a background to the development of successful public health activity. You will recall from the introduction to Section 2 that health determinants are the biomedical, genetic, behavioural, socioeconomic and environmental factors that impact on health and wellbeing. These determinants can be influenced by interventions and by resources and systems (Australian Institute of Health and Welfare (AIHW) AIHW 2012a). Many factors combine to affect the health of individuals and communities. People’s circumstances and the environment determine whether a population is healthy or not. Factors such as where people live, the state of their environment, genetics, their education level and income, and their relationships with friends and family are all likely to impact on their health. The determinants of population health reflect the context of people’s lives; however, people have limited control over many of these determinants (WHO 2007).