Identifying shopping center attractiveness using taxi trajectory data

Customer attractiveness evaluation and classification of urban commercial centers by crowd intelligence

“…In the field of analysis on taxi trajectories, Yue et al present a method to evaluate the attractiveness of shopping center by combining and clustering similar taxi trajectories in terms of drop-offs and pick-ups, and propose to take time dependency among clusters as the standards of clustering [19]. Next, Yue et al take into consideration some new metrics, such as total rented area, the number of shopping centers and parking slots etc., to evaluate the attractiveness of shopping centers [20].…”

“…Kawasaki and Axhausen used GPS data to generate choice set for grocery shopping location choice model [18]. Yue et al presented a method to evaluate the attractiveness of shopping center using the generated trips and the catchment areas [19] [20], based on the taxi trajectories in Wuhan, China. However, there are two points that should be reconsidered in the last study.…”

Understanding the Dynamics of the Pick-Up and Drop-Off Locations of Taxicabs in the Context of a Subsidy War among E-Hailing Apps

“…Third, researchers have used taxicab trajectories to examine land-use types, reflect the spatial structure of urban areas, and examine the interactions between residents and functional zones. Such approaches have been used in, for example, accessibility analysis of urban road networks [27,28], mining alternative space-time path dynamics of travel [29], mining hotspots and points of interest in urban areas [30][31][32], determining the spatiotemporal attractiveness of specific areas [33,34], detection and analysis of functional regions [35][36][37], classification of land-use types [38,39], analysis of the structure of urban regions [40][41][42][43], observing strong links between public transportation terminals [44], evaluating the effectiveness of urban planning after it has been carried out [45], identifying the spatiotemporal patterns of functionally critical locations in urban transportation networks [46], and locating optimal taxi stands on city maps using pick-up and drop-off locations in Singapore [47].…”

Geographical and temporal huff model calibration using taxi trajectory data

“…The ubiquitous rise of shopping malls provides more shopping choices for customers. However, it also causes a series of issues for urban planners, such as high business competition, traffic congestion, and inefficient land use (Yue et al, 2011). To increase positive business competition, reduce traffic congestion, and improve land use efficiency, a possible countermeasure is to predict journeys to shopping areas (Bohnet and Gutsche, 2007).…”

“…The Huff model includes two attributes: a shopping centre's attractiveness, and customer's travel cost. Experiment showed that an attractive shopping mall is considered to have large area, including more requirements for a large range of goods, and is mostly located in city centres; while some people travel to relatively unattractive stores located far from city centres in order to benefit from lower prices (Yue et al, 2011). Previous research has demonstrated that shopping area size, traveller volume and customers' reviews on social media are able to represent shopping area's attractiveness with high performance (Gong et al, 2017;Gong et al, 2018).…”