Search Results (2)

In the last two decades, the retail sector has experienced unprecedented upheaval, having severe implications for economic development and sustenance of traditional inner-city retail districts. In the city of Christchurch, New Zealand, this effect has been exacerbated by a series of earthquakes in 2010/2011 which destroyed much of the traditional retail precinct of the city. After extensive rebuild activity of the city’s infrastructure, the momentum of retailers returning to the inner city was initially sluggish but eventually gathered speed supported by increased international visitation. In early 2020, the return to retail normality came to an abrupt halt after the emergence of the COVID-19 pandemic. This study uses spending and transaction data to analyze the compounding impact of the earthquake’s aftermath, shift to online shopping, and the retail disruption in the Christchurch central retail precinct because of COVID-19. The findings illustrate how consumers through their spending respond to different types of external shocks, altering their consumption patterns and retail mode (offline and online) to cope with an ever-changing retail landscape. Each event triggers different spending patterns that have some similarities but also stark differences, having implications for a sustainable and resilient retail industry in Christchurch. Implications for urban retail precinct development are also discussed. Full article

Short distance travel and commute being inevitable, safe route planning in pandemics for micro-mobility, i.e., cycling and walking, is extremely important for the safety of oneself and others. Hence, we propose an application-based solution using COVID-19 occurrence data and a multi-criteria route planning technique for cyclists and pedestrians. This study aims at objectively determining the routes based on various criteria on COVID-19 safety of a given route while keeping the user away from potential COVID-19 transmission spots. The vulnerable spots include places such as a hospital or medical zones, contained residential areas, and roads with a high connectivity and influx of people. The proposed algorithm returns a multi-criteria route modeled on COVID-19-modified parameters of micro-mobility and betweenness centrality considering COVID-19 avoidance as well as the shortest available safe route for user ease and shortened time of outside environment exposure. We verified our routing algorithm in a part of Delhi, India, by visualizing containment zones and medical establishments. The results with COVID-19 data analysis and route planning suggest a safer route in the context of the coronavirus outbreak as compared to normal navigation and on average route extension is within 8%–12%. Moreover, for further advancement and post-COVID-19 era, we discuss the need for adding open data policy and the spatial system architecture for data usage, as a part of a pandemic strategy. The study contributes new micro-mobility parameters adapted for COVID-19 and policy guidelines based on aggregated contact tracing data analysis maintaining privacy, security, and anonymity. Full article