Although the phenomenon of spatial agglomeration and its associated productivity premium applies to many industries, scholars have only recently considered agglomeration in the tourism industry. To ...avoid overestimation of the agglomeration effect and provide strong empirical evidence for policy formulation related to productivity improvement, we develop a theoretical framework to identify and decompose the contributions of spatial agglomeration to the productivity of hotel and catering enterprises. Using (Abel & Deitz, 2015) Chinese firm-level data for the hotel and catering industry from China's Second National Economic Census in 2008 and (Ahlfeldt & Pietrostefani, 2019) data from the 2007–2011 China Tax Census and 2009–2014 China Key Tax Source Survey, this study finds (Abel & Deitz, 2015) obvious agglomeration effects in the hotel and catering industry and that spatial agglomeration improves the average productivity of such enterprises in large cities; (Ahlfeldt & Pietrostefani, 2019) the competition is more fierce for hotels and catering enterprises in big cities, with high-productivity companies benefitting and low-productivity businesses suffering; (Andersson et al., 2007) low-productivity hotel and catering enterprises in big cities flee to smaller cities, that is, there is a clear sorting effect and (Au & Henderson, 2006) some high-productivity enterprises in big cities have migrated to small cities, indicating negative selection effects. The results of robustness tests validate these conclusions.
•This paper uses the hotel and catering industry (HCI) data from China for study.•The agglomeration effect attributes to HCI's productivity premium in big cities.•High-productivity companies benefit from the fierce competition in big cities.•Low-productivity enterprises in large cities choose to flee to small cities.•Some high-productivity enterprises in the big cities relocate to small cities.
We study a rich production-routing problem with time windows arising at a catering services company. The production part consists of assembling the meals to deliver. It considers release times to ...ensure freshness of the products to be delivered and is also restricted by due times incurred by the constructed routes. Production employee shifts together with a compatible production schedule must be determined. The routing part consists of building vehicle routes that can contain multiple trips and must satisfy customer time windows and vehicle capacity. Routing and production costs, including a guaranteed minimum paid time for the drivers and the production employees, are minimized under various constraints. To solve this complex problem, we propose an exact branch-price-and-cut algorithm. We introduce a new branching rule that imposes on one branch a lower bound on the production costs. Computational results obtained on instances derived from real-world data sets show the effectiveness of this branching rule. Overall, our algorithm is able to solve to optimality instances with up to 25 orders and four products in less than two hours of computational time. To tackle larger instances involving up to 50 orders, we turn the proposed algorithm into a heuristic by avoiding a complete enumeration of the search tree and develop two other matheuristics based on this branch-price-and-cut heuristic.
The online appendices are available at
https://doi.org/10.1287/trsc.2018.0854
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Catering facilities have a significant impact on the environmental sustainability of any destination. While travelling, people waste more food, eat more and prefer environmentally less sustainable ...products. This unsustainable behaviour is spatially conditioned: tourists move almost exclusively within a small part of a destination (the so-called limited area) where only a limited number of catering facilities are located. These businesses are therefore the key drivers of the environmental sustainability. The main objectives of this paper are to investigate the size of the limited area, number of catering options spatially accessible to tourists and finally to assess the environmental vulnerability of 38 European destinations associated with the limited area tourists usually visit and with the number of catering facilities that are accessible for tourists. Based on the spatial analysis considering the location of catering facilities, geo-located photographs and Airbnb listings, the limited area was calculated, and four indicators were implemented to assess the environmental vulnerability. The results showed that tourists move in only 4.4 km2 (3.3% of a city administrative boundary). In this area, millions of tourists have access to 685 catering facilities. In terms of spatial conditionality of food consumption, Venice, Amsterdam, and Florence are among the most environmentally vulnerable destinations. Furthermore, Venice and Florence also lack the environmental potential as a strong majority of catering facilities is located within their limited areas. On the contrary, Geneva and Thessaloniki were assessed as the least environmentally vulnerable destinations in our sample. Paris is the destination with the highest environmental potential, as 84% of its catering businesses are located beyond the borders of the limited area.
The development of O2O (online to offline) e-commerce and instant delivery has not only made it easy to access information, but also it has overcome the limitation of walking distance, promoting the ...transformation of traditional commercial space and making online catering a common form of food consumption. Studying the spatial distribution of urban catering industry under new technologies is helpful to understand the current development of the catering industry, which is of great significance for guiding the development of the catering industry. However, the trend and mechanism of changes need to be further studied. Based on the spatial distribution of urban catering industry, this study establishes a framework for analysing offline and online catering spaces. In this framework, big data are used to conduct GIS kernel density analysis and spatial autocorrelation analysis to investigate the spatial distribution laws of the catering industry, and multinomial logistic regression analysis is applied to explore the main factors influencing location selection of offline and online catering spaces. The main results include the following: (a) the new pattern of catering space still follows the traditional location selection theory and (b) population density and road network density are the main factors affecting the catering space in Shenzhen.
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