Purpose: The purpose of this study is to assess the evolution of restaurant locations in the city of Hamilton over a 12-year period (1996 to 2008) using GIS techniques. Retail theories such as central place, spatial interaction and principle of minimum differentiation are applied to the restaurant setting. Design/methodology/approach: A database of restaurants was compiled using the NZ yellow pages and contained 981 entries that consisted mainly of location addresses and types of cuisine. This paper focuses on locational patterns only. Findings: A process of geo-coding and clustering enabled the identification of two clustering periods over 12 years for city restaurants, indicating locational patterns of agglomeration within a short walking distance of the CBD and spill over effects to the north of the city. Research limitations/implications: The data do not allow statistical analysis of the variables causing the clustering but offer a visual description of the evolution. Explanations are offered on the possible planning regimes, retail provision and population changes that may explain this evolution. Practical implications: The findings allow identification of land use patterns in Hamilton city and potential areas where new restaurants could be developed. Also, the usefulness of geo-coded data in identifying clustering effects is highlighted. Originality/value: Existing location studies relate mostly to site selection criteria in the retailing industry while few have considered the evolution of restaurant locations in a specific geographic area. This paper offers a case study of Hamilton city and highlights the usefulness of GIS techniques in understanding locational patterns.
LINK
Tipping is a social norm in many countries and has important functions as a source of income, with significant social welfare effects. Tipping can also represent a form of lost tax revenue, as service workers and restaurants may not declare all cash tips. These interrelationships remain generally insufficiently understood. This paper presents the results of a comparative survey of resident tipping patterns in restaurants in Spain, France, Germany, Switzerland, Sweden, Norway, and the Netherlands. ANOVA and ANCOVA analyses confirm significant variation in tipping norms between countries, for instance with regard to the frequency of tipping and the proportion of tips in relation to bill size. The paper discusses these findings in the context of employment conditions and social welfare effects, comparing the European Union minimum wage model to gratuity-depending income approaches in the USA. Results have importance for the hospitality sector and policymakers concerned with social welfare
MULTIFILE
Social media are rapidly becoming a viable way of service marketing and customer engagement in the hospitality industry. Facebook, for instance, allows restaurants to publish information, multimedia content and engage with their customers e.g., to answer questions or learn about their preferences. Being active on social media has become increasingly important as customers more frequently turn to social media and the Web for restaurant reviews before deciding to visit (Lewis and Chambers, 2000).
DOCUMENT
The focus of this project is on improving the resilience of hospitality Small and Medium Enterprises (SMEs) by enabling them to take advantage of digitalization tools and data analytics in particular. Hospitality SMEs play an important role in their local community but are vulnerable to shifts in demand. Due to a lack of resources (time, finance, and sometimes knowledge), they do not have sufficient access to data analytics tools that are typically available to larger organizations. The purpose of this project is therefore to develop a prototype infrastructure or ecosystem showcasing how Dutch hospitality SMEs can develop their data analytic capability in such a way that they increase their resilience to shifts in demand. The one year exploration period will be used to assess the feasibility of such an infrastructure and will address technological aspects (e.g. kind of technological platform), process aspects (e.g. prerequisites for collaboration such as confidentiality and safety of data), knowledge aspects (e.g. what knowledge of data analytics do SMEs need and through what medium), and organizational aspects (what kind of cooperation form is necessary and how should it be financed).Societal issueIn the Netherlands, hospitality SMEs such as hotels play an important role in local communities, providing employment opportunities, supporting financially or otherwise local social activities and sports teams (Panteia, 2023). Nevertheless, due to their high fixed cost / low variable business model, hospitality SMEs are vulnerable to shifts in consumer demand (Kokkinou, Mitas, et al., 2023; Koninklijke Horeca Nederland, 2023). This risk could be partially mitigated by using data analytics, to gain visibility over demand, and make data-driven decisions regarding allocation of marketing resources, pricing, procurement, etc…. However, this requires investments in technology, processes, and training that are oftentimes (financially) inaccessible to these small SMEs.Benefit for societyThe proposed study touches upon several key enabling technologies First, key enabling technology participation and co-creation lies at the center of this proposal. The premise is that regional hospitality SMEs can achieve more by combining their knowledge and resources. The proposed project therefore aims to give diverse stakeholders the means and opportunity to collaborate, learn from each other, and work together on a prototype collaboration. The proposed study thereby also contributes to developing knowledge with and for entrepreneurs and to digitalization of the tourism and hospitality sector.Collaborative partnersHZ University of Applied Sciences, Hotel Hulst, Hotel/Restaurant de Belgische Loodsensociëteit, Hotel Zilt, DM Hotels, Hotel Charley's, Juyo Analytics, Impuls Zeeland.
