Modelling tourism and hospitality employment clusters: a spatial econometric approach

• Published in: Tourism geographies 2017-05, Vol.19 (3), p.398-424
• Main Authors: Chhetri, Anjali, Chhetri, Prem, Arrowsmith, Colin, Corcoran, Jonathan
• Format: Article
• Language: English
• Subjects: Econometrics; Economic models; Employment; GIS; spatial autocorrelation; Spatial cluster; Tourism; tourism and hospitality sector; 地理信息系统; 旅游酒店部门; 空间自相关; 空间集群
• ISSN: 1461-6688; 1470-1340
• DOI: 10.1080/14616688.2016.1253765

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.