Qualitative benefits of MBESST in the selection of a restaurant location: Touristic restaurant Palencia de Lara, Toledo, Spain

Mauro Felipe Berumen Calderón (), Damayanti Estolano Cristerna (), José María Vallejo Herrera () and Ricardo Sonda de la Rosa ()

International Journal of Innovative Research and Scientific Studies, 2024, vol. 7, issue 2, 472-486

Abstract: Selecting the optimal location for a restaurant is a process that demands crucial and comparable data. The Model for the Best Site Selection for a Restaurant (MBESST) is a flexible model that combines quantitative and qualitative elements in assessing any restaurant site. This research provides the qualitative results derived from evaluating the location of an empirical case, Palencia de Lara Restaurant in Toledo, Spain, a tourist city. The design consisted of a non-experimental, transversal, and qualitative approach, using non-participant observation and interviews to gain a desirable appreciation of the issue. The global assessment's locations were 7.26, indicating the collection of essential components to maximize its appeal to guests. Palencia de Lara Restaurant should optimize its entire operational capacity more effectively. Flow pattern, visibility, and massive traffic generators were the three most essential factors in selecting this location. A significant contribution of the research is that using the definitions of the factors and sub-factors and the scale of specific quality levels allows for focusing on standard terms during the location assessment process. The designed instruments in the MBESST facilitate users to get an integral assessment of any locations of nine factors, fifty-one sub-factors, and individual quality levels of the sub-factors, enabling an in-depth analysis of each assessed element and comparing each other under the same parameters, gathering quantitative and qualitative data.

Keywords: Analytic hierarchy process; Analytic rubric; Independent restaurant; Location assessment; Model BESST; Restaurant industry; Restaurant location; and Tourist businesses. (search for similar items in EconPapers)
Date: 2024
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