Call of the Mall: The Geography of Shopping

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Where Should We Build a Mall? In spite of the recent surge in e-commerce, brick-and-mortar retail, specifically in the form of large-scale shopping malls, is still the dominant venue for consumer purchases in the developed world. The construction of mass-scale shopping malls has also experienced tremendous growth in newly industrialized countries such as China. This research provides a rigorous, yet practical, framework to understand and evaluate why retail stores join a shopping mall and how their decisions affect mall revenue. The model can be extended and applied to a number of settings where a decision maker must choose among alternative sites to construct a market, for example, for transportation hubs such as airports or train stations.

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Author Abstract. Finally, this study advances the knowledge basis in this area by adding evidence of one of the most visited shopping centres in Stockholm, the capital of Sweden—contributing therefore to the international literature on this area. The structure of the article is as follows.

Crime in a Scandinavian Shopping Centre

First, the shopping centre as a criminogenic place is discussed followed by a review of the potential of using 3-D visualization techniques in research and practice. The case study is framed followed by a description of the methods. Then, the nature, levels and patterns of crime and public disturbance in the shopping centre over time and space are presented.

The chapter concludes by bringing together the evidence from a fieldwork inspection to the evaluation provided by the 3-D visualisation as well as suggestions for improving the environment of this shopping centre using CPTED principles as a theoretical reference. These may arise from complex dynamic interactions among individuals—offenders and controllers, mediated by the types of environments including targets they are exposed to.

Five perspectives suggest the importance of places for understanding crime: rational choice; routine activity theory; crime pattern theory; social disorganisation theory and Crime Prevention Through Environmental Design CPTED. Although these perspectives are mutually supportive, the first three perspectives provide different explanations for crime occurring at different places, the fourth considers the importance of context for explaining high crime areas in risky facilities and the fifth theory provides micro-environmental clues for why crime occurs in particular places.

Finally, three other types of controllers—intimate handlers, guardians and place managers Felson, , , , must be absent or ineffective. Felson suggests that multiple actors exercise social control: handlers who control potential offenders, managers who control places, and guardians who control targets.

In the case of youngsters at a shopping centre, handlers could be older siblings or store personnel. There could be two types of guardians in a shopping mall: formal guardians whose responsibility is to protect targets people and property from crime, such as police officers, security guards and store controllers, and informal guardians, including employees or other customers in a store. If the target is an individual then guardians can be family members, friends and others who are at the same place as the target.

Place managers can be shopping personnel, guards, or parking lot attendants—they regulate behaviour at the locations they control. A thief may give up stealing a purse if s he notices that s he is being watched by a restaurant employee. In real life, there are overlaps between the role of handlers, guardians and place managers among those who work at a shopping mall.

There may also be crime promoters —people who inadvertently, carelessly or deliberately make crime more likely to happen. Yet, these opportunities for crime do not happen at random in time and space. Thus social disorganisation theory can contribute to understanding the links between risky facilities, such as a shopping centre, in a wider geographical context. One reason is that they may be located in criminogenic areas, places that have a disproportionate number of opportunities.

Another reason is that, as with city centres, shopping malls also have alcohol selling premises, bowling and cinemas, which generate activities that reproduce problems, associated with the city centre, in particular, night life crime. One of the seminal studies with shopping centres was performed by Engstad He found that areas with shopping centres had higher rates of crime per thousand population than areas without shopping centres. Note that traditionally crime generators are particular areas to which large numbers of people are attracted for reasons unrelated to any particular level of criminal motivation they might have or to any particular crime they might commit.

Examples include shopping and entertainment areas while crime attractors are particular places or neighbourhoods to which strongly motivated offenders are attracted due to the known opportunities for particular types of crime. Examples might include bar districts, prostitution areas, and drug markets. The type of building and architectural design influences what occurs in them and in their surrounding environments.

Ceccato, ; Loukaitou-Sideris, and parks e. Crime and safety in shopping centres: a conceptual model.

Online shopping vs. mall shopping

Source: Ceccato b. Functional spaces are those spaces which have a defined function in the shopping mall, such as stores, restaurants, banks or toilets. How much they are exposed to crime depends on their location in the mall but also internal and external features such as good lighting, design and positions of doors, windows and stair cases, entrances. These features may reduce the possibility of crime occurring by stimulating surveillance, fostering territoriality and reducing areas of conflict by controlling access from outsiders Ekblom, , , ; Jeffery, ; Newman, ; Poyser, The vulnerability of a particular store depends on its layout, its management and the types of goods sold.

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  • Bars, pubs and restaurants, for example, may become source of problems when the shopping mall closes down. Jewellery stores and retail with high valued goods e. After school hours might attract youngsters to particular settings at shopping mall, often with no guardians around e.

    Call of the Mall: The Geography of Shopping by the Author of Why We Buy

    Open public spaces in a shopping mall have a key role in terms of safety as they are settings of convergence at all times. For instance, in a food court they may create obstacles, obstructing the field of view of clients. Open paths dividing food courts, stores and restaurants create unnecessary opportunities for thieves as they allow non-clients to have access to their premises. Shopping centres also have transitional areas , such as corridors, stairs and paths. Length and width, location, types of materials, enclosure and design, all affect how safe these transitional areas are.

    Corridors often have obstacles placed in locations that might offer criminals opportunities to commit a crime and then hide Newman, Examples of these obstacles can be temporary shops, permanent pillars or furniture, blocking the view of transients. They can themselves be a target of crime as people might steal goods. Demonstration stalls at corners and in public spaces in the shopping centre help visitors to get to know new products but also to become distracted, and as a consequence, becoming themselves an easier target for thieves.

    Corridors might be straight and in peak visiting hours, they can be a source of irritation as well as places for bag snatching and pickpocketing. Moreover, if anyone is allowed in the area, this might create a sense that nobody is in control. The entrances carry the identity of the shopping centre. They can be of many types, for pedestrians or for cars, giving access to the parking lot. In any case, well-functioning entrances allow the flow of people or cars , both under normal and emergency conditions.

    Using semi-transparent materials and glass in the construction of entrances allows good sunlight illumination and may affect natural surveillance.

    Call of the Mall: The Geography of Shopping by Paco Underhill

    The entrances are also the connection of the centres with the rest of the city. The number of entrances varies with the size of the shopping centre. More entrances in problematic neighbourhoods may mean more crime. Bowers suggests that there is a positive relationship between internal and external crime in an area. Failed security systems in parking lots bring in individuals that would not have the right to be in the premises, including thieves. Inner city shopping centres may be extra vulnerable to crime spill-over from mixed land use, with bars and restaurants.

    How to measure footfall?

    Once each unique location was identified, the user was capable of assigning incidents to each location. In this simple approach, incidents were plotted in the centre of each location with the symbol designating the number of incidents that occurred in that location over a designated time period.

    Later on, they developed an advanced GIS approach to visualise in more detail and with more accuracy the crime location e. Yet, while the capacity to visualise incidents onto a digital map provides a wealth of possibilities, Rengert and Ratcliffe concluded that it also created some barriers to effective analysis, such as increased software and training costs and problems with the identification of repeat victimization. Moreover, they did not explore the temporal dimension of crime incidents across the 3-dimensional space.

    Taking the previous work by Rengert and colleagues, this study takes a step forward by testing a prototype with new visualisation tools BIM and explores the temporal dimensions of crime in space in a shopping centre. However, BIM as a term can be misleading. As suggested by Bisio , BIM is not just about buildings, it is a process that enables efficient and quality design, construction and operation of a structure such as a building e.

    One of the most appreciated capabilities provided by BIM is high-end 3-D visualization. No previous research has tested the use of BIM for visualizing and analysing criminal occurrences inside buildings, such as a shopping centre. This shopping centre includes stores from the most important Swedish chains. The mall is frequented both weekdays and weekends, with around 60, and 45, visitors per day, on average , a week.

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    • There is also a large library and a hotel. The mall is formed with a main entrance in the middle of the building. There are two floors, a main floor where most of the activities are available and an upper floor where some shops, a restaurant and cinema are sited. In the middle of the building is the shopping heart, the food court with some 20 restaurants. There are eight entrances of different sizes. What is also relevant from a criminogenic perspective is that in the middle of the aisles too some activities are situated, including telemarketers, sweet stores and cafes.

      This dataset was used because police records cover just a minor portion of total incidents, for shoplifting is only 2 percent of the total, for example Swedish Trade Federation, The data is gathered by the company in charge of security services in the mall. There are different ways of reporting crime and incidents of crime and disorder. Incidents other than crime are also recorded in the same database. The security company does not cover the parking lots, and incidents that take place there are not included in this dataset. Supermarkets are open from to while bars are open from to Data collected through fieldwork inspection performed in a series of visits to the shopping centre in particular environments most targeted by crime and incidents of public disturbance.

      In order to obtain a better understanding of the nature of crime concentration in space and time in a shopping centre, a 3-D visualisation using BIM was combined with fieldwork inspection. An object-oriented model of the entire building was constructed based on the drawings using a proprietary BIM-authoring software application Autodesk Revit 1. Next, underlying plan drawings were used for creating a three-dimensional model of the building at a relatively low level of detail.

      The levels of detail of the model were based on three level scales: the macro-scale: the overall system the shopping centre ; the meso-scale a floor ; and the micro-scale: settings in a location e. Each floor was considered a separate layer connected by limited access corridors or ways elevators and stairs that could also be visualised together and be the basis for analysis. Then, the next step was to populate this model with crime data. Through an iterative process, both the model and XML reports were synchronised to reflect the total number of events per room.

      First, a standardized list of crime types was used for interpreting the descriptive texts through reports. After several trials using different filters, 90 percent of crime occurrences and incidents of public disturbance were mapped in the model. Cylinders were used to represent the volume or rates of crime by location in each store.

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      In order to visualise crime by location and over time, a tool was programmed allowing three 3-D mapping modes: Choropleth 3-D map —The size of the cylinder corresponds to the absolute number of crimes per type and location. This feature is useful to compare particular sections of data by crime type, for instance, peak hours versus off-peak hours. Stacked cylinder map —The size of cylinder is standardized by percent total crime by each individual location in space and is split by the proportion of each crime incident absolute numbers for each crime location.

      Scaled map —The most important advantage of this mode is that it indicates a unique specialization of crime incidents by location, for instance, violence dominates security guard calls for service in bar A while in shoplifting and thefts dominate calls in supermarket B. In all modes, the tool makes it possible to filter crime incidents by time slices, for instance, to visually check sections of the data by day or hours of the day.