Spatial optimisation of fire service coverage: a case study of Brisbane,Australia

In the context of changing demand for fire services, spatial optimisation of fire coverage has attracted little scholarly attention despite its potential to improve emergency response and to inform future service planning for fire stations. Drawing on small area population forecasts, this paper extends the application of the Maximum Coverage Location Model to compute and delineate the spatial coverage of current and proposed new fire stations to align with population growth estimates for Brisbane, Australia. Our results reveal important gaps in fire cover that are likely to emerge as a result of predicted population growth, the spatial patterns of which varies across the Brisbane metropolitan area. We draw on these results to delineate a series of new potential sites for fire stations to ameliorate the reduction in spatial coverage as a consequence of predicted population growth demonstrating the utility of our analytic approach for decision‐making and operational planning in the fire services.     

Modelling tourism and hospitality employment clusters: a spatial econometric approach

ABSTRACT

Geographic clustering of industries for mutual economic benefit has long been recognised. The concept of ‘externalities’ introduced by Alfred Marshall early last century rely on agglomeration of specialised industry within a geographic area. However, only recently has cluster modelling been applied to the tourism and hospitality (T&H) industry. The aim of this paper, therefore, is twofold: first is to develop a cluster-based theoretical framework for delineating geographic boundaries of T&H clusters, and second is to identify the underlying factors that drive their form and shape.

Drawing on employment data as the basis for co-location of T&H firms, spatial econometrics techniques are applied to model the spatial clustering of T&H employment in Victoria, Australia. Results show that rural tourism regions have higher levels of employment in tourism operational services whereas employment in city-based regions is more concentrated in hospitality services. Our findings, when normalised as a percentage of total employment, show that rural and regional Victoria ranks most highly as employers in the T&H industry. Adopting a range of spatial metrics, we show that T&H clustering throughout Victoria is largely driven by six location-specific factors: (1) the availability of tourism attractions; (2) proximity to the coast; (3) the road density network; (4) accessibility to employment within the Melbourne CBD; (5) the scale of the regional economy; and, (6) the advantages and disadvantages associated with economic resources. We conclude that the cluster-led strategy pose a number of challenges for tourism planners to promote regional tourism. Nevertheless, results from this study indicate that T&H employment clustering creates a more cohesive spatial structure that could support economic development and better connectedness of tourism destinations. These clusters could act as service hubs to their wider catchment areas where visitors are encouraged to stay overnight and travel to specific sights during the day.     

Exploring a Relationship Between Aggregate and Individual Levels Spatial Data Through Semivariogram Models

Analysis of social data is frequently done using aggregate-level data. There may not be a direct interest in spatial relationships in the data, but the presence of spatial interdependence may still need to be taken into account. This article explores the aggregation effect from a spatial perspective by assuming nonzero covariance for individual data from two different groups. We investigate the bias associated with aggregate-level data for semivariogram analysis. We show that the bias mainly arises from the average of the semivariogram within the groups. It is also shown how aggregated-level data may be used to estimate parameters of an individual-level semivariogram model. A nonlinear regression method is proposed to carry out this estimation procedure and a simulation is done to clarify the results.