To cluster or not to cluster?: Understanding geographic clustering by restaurant segment |
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| Institution: | 1. School of Hospitality and Tourism Management, Purdue University, 900 W State Street, Marriott Hall, Room 206, West Lafayette, IN 47907-2115, USA;2. School of Hospitality and Tourism Management, Purdue University, 900 W State Street, Marriott Hall, Room 245, West Lafayette, IN 47907-2115, USA;1. Rosen College of Hospitality Management, University of Central Florida, 9907 Universal Blvd., Orlando, FL, 32819, United States;2. Rosen College of Hospitality Management, University of Central Florida, Orlando, FL, United States;1. Department of Business and Accounting, Faculty of Economics and Business Administration, Universidad Nacional de Educación a Distancia (UNED), Paseo Senda del Rey, 11, 28040 Madrid, Spain;2. Department of Business and Accounting, Faculty of Economics and Business Administration. Universidad Nacional de Educación a Distancia (UNED), Paseo Senda del Rey, 11, 28040 Madrid, Spain;1. School of Marketing, Ehrenberg-Bass Institute for Marketing Science, University of South Australia, Adelaide, Australia;2. Department of Agricultural Economics, Stellenbosch University, Stellenbosch, South Africa;1. Ecole hôtelière de Lausanne, HES-SO//University of Applied Sciences Western Switzerland, Route de Cojonnex 18, 1000, Lausanne 25, Switzerland;2. Columbia University, 701 Uris Hall, New York, NY, 10027, United States |
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| Abstract: | This study tested whether geographic clustering differs by restaurant segment due to the differences in consumers’ hedonic and utilitarian values by using Ripley’s K function and a Tobit model. This study found that higher priced restaurant segments have stronger clusters than lower priced restaurants, which implies that restaurants that focus on hedonic values tend to cluster more than utilitarian focused restaurants. However, the results differ depending on whether or not restaurants are located within a central business district (CBD). For example, quick service restaurants have stronger clusters than casual restaurants outside CBDs. Practical applications may apply to new restaurants that are attempting to open. Up-scale restaurants have the advantage of reducing research costs by locating near similar restaurants. Moreover, casual restaurants do benefit by clustering near existing ones under the condition that demand is not severely hurt by competition, while quick service restaurants benefit by diffusing from each other. |
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| Keywords: | Restaurant segments Agglomeration Clustering Hedonic Utilitarian Central business district |
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