ABSTRACT
In this research, we analyzed the delivery service areas of restaurants, customer satisfaction, and restaurant sales of urban restaurants during the COVID-19 pandemic. We obtained the datasets on food ordering options and restaurant rankings based on Google Maps, Open Street Map, and widely known online food order applications in Iran. Based on this analysis we further modeled suitable areas for future extension of restaurants. We analyzed the online food order data of restaurants' sales and food delivery reports for 1050 restaurants in the city of Tabriz. We collected and analyzed data on the restaurant locations, the number of food orders for each restaurant, and the number of customers and their locations. Our results revealed that the spatial dimension of the newly emerging food delivery areas is of utmost importance for the success of restaurants. This indicates that an optimal location is not longer only dependent on factors like population density and competitors in the direct vicinity but on the services density even from more distant competitors. The results indicate that an optimized spatial distribution of the restaurants together with efficient quality in services can contribute to optimistic urban development. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
ABSTRACT
In the COVID-19 pandemic era, undoubtedly mathematical modeling helps epidemiological scientists and authorities to take informing decisions about pandemic planning, wise resource allocation, introducing relevant non-pharmaceutical interventions and implementation of social distancing measures. The current coronavirus disease (COVID-19) emerged in the end of 2019, Wuhan, China, spreads quickly in the world. In this study, an entropy-based thermodynamic model has been used for predicting and spreading the rate of COVID-19. In our model, all the epidemic details were considered into a single time-dependent parameter. The parameter was analytically determined using four constraints, including the existence of an inflexion point and a maximum value. Our model has been layout-based the Shannon entropy and the maximum rate of entropy production of postulated complex system. The results show that our proposed model fits well with the number of confirmed COVID-19 cases in daily basis. Also, as a matter of fact that Shannon entropy is an intersection of information, probability theory, (non)linear dynamical systems and statistical physics, the proposed model in this study can be further calibrated to fit much better on COVID-19 observational data, using the above formalisms.