Smart cities and flagship stores: lighting and contract

The GOAL of the Report 'Smart cities and flagship stores: lighting fixtures' is to provide: Lighting companies with a tool to identify potential locations where to set their mono-brand stores, keeping into account potential synergies (for instance the presence of complementary brands) as well as an indicator of the cost of the area; The industry, in general, with an analysis on the medium-term trends affecting the main cities worldwide. DESCRIPTION: The Report provides profiles of 85 cities worldwide with a selection of economic and demographic indicators (2013 and 2018), estimates of the potential market for lighting fixtures, in each city and the forecasts for the market development to the year 2023. The study also offers an analysis of the geographical presence of a selected sample of 65 brands, each of which operates as a trend-setter in its own category. Each identified location is characterized by its type (store, multibrand store, shopping centre) and the cost of the area in which they are located. The aim is, thus, to provide a comprehensive view of the cities that a selection of international retailers entered. Finally, each profile presents a selection of lighting stores and their geographical distribution. In order to identify the position of each of these players in the selected cities, CSIL employed the technique of web scrapping. WEB SCRAPING (also called web harvesting, or web data extraction) is an IT technique of extracting data from a website using software programs. Usually, such programs simulate human browsing on the World Wide Web using the Hypertext Transfer Protocol (HTTP) or through browsers. After applying a system of filters, we managed to identified 4,809 locations across 85 cities. Each location has been further characterized with two additional information: the type of store and the cost of the area. Using metadata, formatted addresses, and GPS coordinates, we managed to define whether the location is a store, a multi-brand retailer, or it is sited in a shopping centre. The residual category, 'Else', includes all the other type of locations: offices, warehouses, distribution centre, etc. Secondly, we managed to associate per each location the cost of the area in which it is sited. The cost is given by a proxy that is the average price of the hotel rooms per night for two persons in a given date (ante Covid-19) of all the hotels positioned within 1 km from the selected location. The price of the hotel rooms, their names and locations were collected implementing a second web-scraping tool. We managed to download the references for 71,132 hotels in 148 cities, no data were available for Tehran (Iran) and Khartum (Sudan). Then, the results were grouped into four categories: 'Very Cheap' (smaller than the first quartile), 'Cheap' (between the first and the second quartile), 'Expensive' (between the second and the third quartile), 'Very Expensive' (higher than the third quartile). The same SPECIAL ANALYSIS was implemented for the 85 selected cities focusing on furniture stores only. We geocalized the presence of 30 leading lighting brands in the selected cities. In addition, we look for the outlets registed with the metadata 'lighting store'. After applying a system of filters, we managed to identified 3,008 locations across 84 cities. No data are available for Tianjin (China). Each location is characterized by the distance from the city centre (in Km), the number of reviews available on Google, the average value of these reviews (from 1 to 5), the website of the store whenever available. For each CITY PROFILE, the following data, indicators and forecasts are provided: Population and its rank within the sample, 2013, 2018 and 2023; Households and its rank within the sample, 2013, 2018 and 2023; Gross domestic product per capita and its rank within the sample, 2013, 2018 and 2023; Household’s consumption per capita and its rank within the sample, 2013, 2018 and 2023; Gross domestic product and its rank within the sample, 2013, 2018 and 2023; Household’s consumption and its rank within the sample, 2013, 2018 and 2023; Breakdown of households by the level of income, 2013, 2018 and 2023; Lighting fixtures demand and its growth rate, 2013, 2018 and 2023; Lighting store sales (factory price) and its growth rate, 2013, 2018 and 2023; Spatial analysis of the distribution of 50 brands within the city map; Spatial analysis of the distribution of lighting outlets within the city map. In order to minimize the problems arisen by the lack of a unique definition of city, CSIL decided to use demographic and economic data coming from a unique source, namely C-GIDD (www.cgidd.com). We access that database in January 2020, therefore macroeconomic estimations and forecasts were made before that date. The world has changed dramatically in the recent months as the world has been put in a Great Lockdown. According to the IMF, 'the magnitude and speed of collapse in activity that has followed is unlike anything experienced in our lifetimes'. Up to the publication date of this report updates on forecasts up to 2023 haven’t be released. The only updates concern 2021. According to the IMF, 'assuming the pandemic fades in the second half of 2020 and that policy actions taken around the world are effective in preventing widespread firm bankruptcies, extended job losses, and system-wide financial strains, we project global growth in 2021 to rebound to 5.8%. This recovery in 2021 is only partial as the level of economic activity is projected to remain below the level that we had projected for 2021, before the virus hit'.