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.

摘要

学术界早已认识到产业部门为经济互利而在地理空间中集聚的现象。上世纪早期, 阿尔弗雷德·马歇尔引入外部性概念, 就建立在特定产业在地理空间集聚的基础上。但是, 直到最近, 集群建模的思想才应用到旅游酒店业中来。因此, 本文研究目的有两个方面:首先, 基于集群的思想发展一个描述旅游酒店集群地理边界的理论框架 ; 其次, 识别形成旅游酒店集群形态的内在驱动因素。

我们以就业数据为旅游酒店集群共同区位的依据, 应用空间计量经济方法模拟澳大利亚维多利亚州旅游酒店产业的空间集聚。结果显示, 乡村旅游地区旅游企业有较高的就业水平而城市地区的就业集中在酒店企业。如果把就业数据标准化为总体就业比例, 我们的研究结果显示, 维多利亚乡村地区位居该地区旅游酒店业最大的雇主。我们采取了一系列空间矩阵, 结果表明, 维多利亚旅游酒店业集群很大程度上受6个特定的区位因素影响༚1(距离旅游吸引物近便 ; 2)邻近海岸 ; 3(稠密的道路网络 ; 4)易于在墨尔本中心商业区就业 ; 5(区域经济规模 ; 以及6)经济资源的优势与劣势。

我们的结论是集群导向的经济战略给旅游规划人员宣传区域旅游提出了许多挑战。但是, 本研究的结果表明, 旅游接待就业的集群创造了一个更紧凑的空间结构, 促进经济发展和旅游目的地之间更紧密的连接。这些集群对广大的腹地区域来说承担着服务枢纽的作用, 鼓励游客在腹地区域逗留过夜同时向具体景点作当日往返的旅行。

KEYWORDS:

• Spatial cluster
• tourism and hospitality sector
• employment
• GIS
• spatial autocorrelation

关键词:

• 空间集群
• 旅游酒店部门
• 就业
• 地理信息系统
• 空间自相关

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Anjali Chhetri

Anjali Chhetri is a tourism analyst. Her current research interests include destination management, tourism planning, international business, cluster, innovation and globalisation, and employment and labour market analysis. She teaches at RMIT and Central Queensland University in Melbourne.

Prem Chhetri

Prem Chhetri is a professor of logistics and geographic systems at RMIT University in Australia. His recent research focused on urban modelling, tourism potential mapping, emergency response, skills and training, and the application of GIS and GPS in transport, infrastructure and tourism planning.

Colin Arrowsmith

Colin Arrowsmith is an associate professor at RMIT University. His research has concentrated on the application of spatial information systems, including geographic information systems (GIS), to investigating the impact of tourism on nature-based tourist destinations as well as employing GIS into the visualisation and analysis of cultural data (in particular cinema studies).

Jonathan Corcoran

Jonathan Corcoran is a professor at the University of Queensland. His previous appointments include the University of Glamorgan (UK) and the UK national mapping agency, Ordnance Survey. Jonathan's research interests lie in the application of quantitative geographical methods for urban modelling in addition to the use of geo-analytical, geo-visualisation and prediction techniques.