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Investigate the shopping centres of the Kingston Area and their patterns of use.

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Introduction

Aim: To investigate the shopping centres of the Kingston Area and their patterns of use. Introduction Kingston Upon Thames is a large Royal borough situated in the South west of Greater London. There are many shopping centres situated within the borough of Kingston that I will be investigating. Kingston town centre is the main focal point in this area as it is clearly larger then any of the other outlying town. We will be analysing the patterns of use for each of the various shopping centres and will then draw conclusions. The shopping centres in which we will be investigating are Kingston Town Centre, New Malden High Street, Kingston Road, Richmond Road, Ham, Surbiton, Surbiton Park Parade, Burlington Road, Chiltern Drive, Alexandra Drive and Villiers Avenue. Here is the Kingston Area in relation to London: On the next page is a map of the Area of Kingston our investigation will be taking place in (Fig.1). Chosen Hypotheses: 1) The Larger the shopping area: - the larger the sphere of influence - the greater the average travel time - the more services present I have chosen this hypotheses because it is obvious that the larger shopping centres will have more shops and services, thus they attract more people, causing the sphere of influence to increase, which in turn causes the average travel time to the shopping centre to increase. 2) People will visit different shopping centres for different goods at different frequencies. ...read more.

Middle

Fig. 3 is a typical image illustrating the Urban Shopping Hierarchies. Data collection/methods I chose these hypotheses as a means of investigating the aim of my investigation. I also used my geographical knowledge of the Central place theory and Urban Shopping Hierachies to base my all my hypotheses on. The last two hypotheses however are general tests, where plenty of data can be generated to obtain a series of results that I can analyse and draw conclusions from. I obtained each of my hypotheses through a series of class discussions with my fellow colleagues. There is a varied array of data and information that is needed to complete this investigation. Below is a list of types of information that are needed together with an explanation of why each is needed: Types of Shops in each shopping centre I need to find out how many different types of shops there are in each shopping centre so I can contrast the different attractions of each centre and see which one offers the most high order shopping and provides the most services. This data is linked to all my hypotheses. Type of Goods Purchased I need to find out what people mostly shops for in each of the shopping centres to give me an idea of what people use each centre for in terms of high and low order goods together with services. This is linked to my second hypotheses. ...read more.

Conclusion

6). Each group were issued both of these sheets for data collection: (Fig.5). The Shopping Survey Questionnaire (Fig. 6). The Shops and Services Classification List There are a few problems that arise when carrying out our data collection. When asking where people have come from, the participants in our data collection may feel threatened by the question and may choose not to answer. This may be a problem presented by our method. Also people may be out to purchase items from more than one category that may become a problem when collecting data. Also when completing the shops classifying survey certain shops may be hard to categorize and may fit into more than one group. All these questions that we have asked are general closed-answer questions with a limited number of responses that we generated through class discussion as a means to base our Questionnaire on. We chose to include fixed response questions on the clear majority apart from the question entitled where do you come from? Below are our results obtained from our Data collection. Fig.7 is completely raw data and is taken from all the data collection questionnaires. (Fig. 7) In order to analyse this data we have collected thoroughly it is necessary that we convert all our data into percentages. This will help create graphs for certain conclusion to be dram n from and will allow us to use the Spearman Rank Correlation coefficient. If the data is kept raw relationships and patterns may be harder to find. Shown below, Fig. 8 shows our results from the Data collection converted into percentages: (Fig. 8) 1 ...read more.

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