Hypothesis 1The retailing experience in 'The Oracle' is more enjoyable than at either 'The Broad Street Mall' or the 'High Street'.
The Hypotheses
The purpose of this section is to outline the hypothesis of this investigation and the methodology behind them.
Hypothesis 1
The retailing experience in 'The Oracle' is more enjoyable than at either 'The Broad Street Mall' or the 'High Street'.
The aims of this hypothesis are to investigate what makes a retailing location enjoyable and whether new developments create a better experience than previous developments. Put into contexts of this investigation I am trying to determine if 'The Oracle' provides a better shopping experience than either of the other two locations, and, if so, why? What I hope to achieve from this hypothesis is a concluding statement confirming or disproving the hypothesis. This would be a most useful result as it may show a generic trend throughout the country - this assumption can be made on the basis that new retailing developments are built to similar specifications.
The methodology of this hypothesis are complex, in order to reach a conclusion for the hypothesis, I need to have a quantitative index score for the areas under investigation [AUI] - 'The Oracle', 'The Broad Street Mall' and the 'High Street' - so comparisons can be draw between them. This would require an index that measured retailing experience. There is no such index available; this effectively means that in order to investigate the hypothesis an index must be created. The details of which will be discussed later on.
Hypothesis 2
The location with the lowest RQA index score needs improving, identify the problems and suggest possible solutions.
This hypothesis will be made clearer as the results from Hypothesis 1 are given. If one area of a CBD is suffering as a result of the success of another it can create an economic imbalance with a distinct rich/poor divide being created. This can have a detrimental effect on the city. This hypothesis is focussing on the problems that the lowest RQA index-scoring district is suffering from and to suggest possible solutions. The purpose of this hypothesis is to create a feasible scheme to regenerate the poor scoring district. Methodology will include assessment of overall quality, a study of amenities and a look at land use and possible problems that lie there in.
Geographical Theory
This investigation will be focusing on the three major retailing areas of the Reading central business district (CBD) - 'The Oracle', 'Broad Street Mall' and the 'High Street*' and the relationship they have with one another.
The aims of the investigation are as follows:
* Investigate the popularity of the three areas and determine which provides the most enjoyable retailing experience.
* Investigate whether there is a clear flow of patterns to one retailing area and try and account for why that is.
* To determine what is being done to improve the worst scoring area.
The investigation is looking closely on the effects of retailing areas on one another. Before we continue it would be appropriate to discus in detail the retail changes in the UK over the last few years.
The pattern of retail change can be broken down into 5 phases. Reading is one of the few examples of an urban area to enter phase 5. In order to understand the significance of this one must look at the initial four phases.
Phase 1 - phase 1 become a general trend of retailing in the 19th century but only in urban areas, it did not take nationwide predominance until the start of the 20th century. Phase 1 is the initial stage of retailing; it is the phase entered when a population moves away from subsistence-level-farming1 and begins to purchase goods on a daily basis from local shops. A shop in a rural/suburban area would specialise in one area of retailing for example a village may contain a butchers, grocers, bakers and a haberdashery. These were generally family run operations and limited in consumer market by the size of the local population. Private transport ownership was not feasible at this period as the technology or infrastructure was not adequate enough to constituter the need for the average villager to own a car. A visit to the city was rare and only for goods that could not be purchased in the local area such as jewellery or for the more affluent, automobiles.
Phase 2 - this phase began in the 1960's as the post war economy began to steady itself; it saw the creation of the retailing 'High Street' that contained non-necessity stores2 and supermarkets.
Supermarkets were a revolutionary new concept located on the suburban/rural-urban fringe. The concept was plausible because of increased levels of private transport ownership and the use of fridge/freezers in the home. These changes meant that the 'bulk buy' initiative could take off; people would be ale to buy the weeks shopping in one go. This was a very popular idea as many people had other commitments such as a full time job and were unable to get food every two or three days. This time period saw the first real chain stores3 being created.
Phase 3 - Phase 3 is more a continuation of phase 2 rather than a totally new idea of its own. This period (1980's) saw the introduction of hypermarkets. Hypermarkets had been widely used in other countries such as America (e.g. Wall-Mart) and France (e.g. Super U). A hypermarket is, for all intents and purposes, a supermarket that has been enlarged to sell other goods beside food e.g. clothing and electrical goods. The idea was that now people really could get everything in one go, you could get the weekly food and buy a new TV and a pair of jeans all in one trip. The concept was viewed as a good idea but not really suited for the UK as these stores had to be much larger to accommodate the increased range of goods and there were not many suitably sized locations. The other major development was the creation of non-food-retail-parks (hereafter referred to as an N.F.R.P).
An N.F.R.P consisted of three or four stores of warehouse design selling non-food goods, such as furniture, large electrical appliances (fridges, ovens) carpets and DIY goods. These parks were constructed on the edge of urban areas to make best use of transport links.
Phase 4 - some viewed this phase as the 'ultimate retailing era'. Taking place in the 1990's. In this phase, the UK saw the construction of regional shopping centres, known as out-of-town retail parks (hereafter known as 'O.O.T.R.P'). These parks were very extensive and often contained more than 200 retail outlets. The centres aimed to provide the most enjoyable retailing experience by incorporating cafés, entertainment and leisure facilities and even hotels into the designs. The idea was to make people feel more at home so they would spend more money.
These O.O.T.R.P's generally had the following characteristics:
Covered for all-weather shopping
Cafes, bars and restaurants
Incorporated entertainment facilities e.g. cinemas and bowling alleys
Massive car parks (the 'Metro Centre' in Newcastle-upon-Tyne has a car park in excess of 10,000 spaces)
Purpose built transport links to motorways and duel carriageways
It was believed by some that these O.O.T.R.P's were too popular and would lead to the economic decline of the CBD. In response to this, the government has imposed restrictions on the size and number of new developments and only a handful of these centres were ever built
Phase 5 - this phase has not been widely shown across the UK; it consists of new retailing centres being constructed within the CBD of major urban settlements. The concept of moving back into the CBD has existed since the early 1990's and was pioneered by the Urban-development-corporations4. Due to restrictions imposed by the government on new developments (see 'Phase 4') and the large areas of derelict land (caused by the outward migration of businesses to these new O.O.T.R.P developments) developers have begun to create new retailing centres within the CBD. These centres were scaled down versions of the O.O.T.R.P's (without the attached leisure facilities) but were built on a similar specification and so share many characteristics with their larger cousins (e.g. being covered, retail outlets, purpose built car parks, large number of shops). Examples of these new CBD Retail centres include 'The Oracle' in Reading and 'Festival Place' in Basingstoke.
As mentioned before this trend cannot be seen across the country but there are many such centres under consideration after the success of the few that have been built.
Following is a detailed look into the history of Reading with particular interest in its retailing and manufacturing.
The History Of Reading
Anglo-Saxon Chronicle for 871 is the earliest evidence for the existence of Reading It was at some time during this period that the Roman roads radiating from Silchester began to be replaced by roads that met in Reading The area was mostly gravel and well-drained, but was close to the rivers, which provided major transport and trade routes.
By the time of the Doomsday Survey (1086), Reading was a borough with a population of 500 or so. It was not important enough to have a castle.
The centre of Reading now moved eastwards. A new road was constructed, and a new bridge over the Kennet, to funnel traffic towards the new Market Place. The major industries were the manufacture of woollen cloth, and of leather. When the site of the Oracle Shopping Centre was being constructed in 1998, an unsuspected discovery was made; a tannery was discovered, below the foundations of the original "Oracle" which was a workhouse for poor cloth-workers.
The industrial Revolution
During this time Reading's position on the waterways and on the Great West Road worked in its favour. Most of the trade was with London. Barges coming up the Thames would turn into the River Kennet to unload at the town wharves, which were lined with timber-yards, warehouses and granaries. The Kennet was made navigable up to Newbury in 1723, and the navigation was extended as the Kennet and Avon Canal, authorised in 1794 and completed in 1810 to give a continuous route between London and Bristol. The importance of Bristol as a port ...
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The industrial Revolution
During this time Reading's position on the waterways and on the Great West Road worked in its favour. Most of the trade was with London. Barges coming up the Thames would turn into the River Kennet to unload at the town wharves, which were lined with timber-yards, warehouses and granaries. The Kennet was made navigable up to Newbury in 1723, and the navigation was extended as the Kennet and Avon Canal, authorised in 1794 and completed in 1810 to give a continuous route between London and Bristol. The importance of Bristol as a port and commercial centre, and Bath as a fashionable resort, led to the improvement of the Great Western Road, which passed through the middle of Reading. In 1801, the population of Reading was about 9,400. By 1851 the population had more than doubled, to 21,500, and at the end of the century, it stood at around 59,000. The town's position, on two railway systems, helped it grow and prosper. The Great Western Rail Road was built first, connecting Reading with London in 1840, and with Bristol in 1841. The Reading, Guildford & Reigate Railway was constructed in 1849
The Twentieth Century
In the first half of the century, Reading was a large, prosperous country town, with some long-established industries and the names of local families on the signboards of town-centre shops.
There was not much damage to its fabric in the two wars,
The story in the second half of the century is one of gradually accelerating growth and change. Reading Borough's population in the 1991 census is given as 135,000. That of the built-up area of Reading was 203,000.
One of Reading's problems in the twentieth century was traffic. Until the opening of the M4 motorway past the town in 1971, it was a notorious bottleneck on the A4. Before the pedestrianisation could take place, through traffic had to be diverted round the town centre, and the controversial solution was the Inner Distribution Road.
Like every other town in the country, the twentieth century has brought about great changes in employment. A number of high-tech companies such as Oracle and Microsoft have located to the town (the area surrounding Reading leading up to Cambridge is often referred to as the European "Silicon Valley"). Other large employers include Prudential, Gillette, and Foster Wheeler. Many of these firms are located in business and industrial parks on the edge of Reading.
At the present day, Reading is a large, prosperous town, with more jobs on offer than there are unemployed people. It draws people in from miles around for employment, education, shopping, and entertainment. To the south, the east and the west there are junctions with the M4 motorway. Its railway station has direct trains to most parts of the country, to Gatwick Airport, and has a coach service to Heathrow Airport. Paddington station is less than half an hour away. Making it one of the most accessible cities in the country.
Methodology
This section includes: a detailed explanation of each of the data collection techniques and those used for analysis, an equipment list and a summary of techniques used in each hypothesis.
Method /
Technique
Equipment used
Justification
Limitations
Retail Quality Assessment
(Blanket study of the AUI)
Note: the details of the RQA index can be found in the accompanying document.
Clipboard, paper, pen
An adaptation of an EQA (environmental quality assessment) focusing on the retailing experience. The RQA was designed specifically for this P.I, as there was no such measure available. A blanket assessment was required because any other type of sampling (stratified, random or representational) may miss buildings that have great influences on visitors. It was therefore necessary for every shop in the AUI to be assessed.
The RQA suffers from subjectivity. This means that what one person may find something to be too bright, another person found it acceptable; the people would therefore give different scores. The RQA would be more successful if completed by several surveyors and average results taken.
Nearest Neighbour Analysis of Amenities (NNA)
Map of AUI, pen, ruler, formula
The NNA gives and indication of the number of services provided for visitors these include things like seating areas and litter receptacles. The survey notes any stratagem behind placement of amenities.
Amenities might not be immediately apparent and some may be overlooked.
Land-Use Map
Map of AUI
A Land-Use Map gives an indication of the varying types of shops in an area. It will be used to assess if nucleation of particular shop types is a reason for poor quality (used for Hypothesis 2).
Clear definitions of what constitutes one category and not another is not always apparent and there is some element of subjectivity. Fortunately the Oracle have already categorised their shops so for the purpose of simplicity one will be using those categories.
Pie Charts
Data from the Land-Use Map
Effective method for displaying large numbers of data, gives a visual impression of the distribution of land use in an area.
Dependent upon accurate data from the analysis of the Land-Use Map any errors will be transferred.
Pedestrian Flow
Paper, pen, stop watch
Pedestrian Flow is the most effective way of gauging the number of pedestrians passing through an area. In this instance it is being observed how many people pass into the AUI. Twenty minutes was selected because with ten sights to assess, it was all that time would permit. Also used to assess numbers entering the shopping centres.
Because each area is being analysed for only twenty minutes, it must be trusted that the data is representational of the area. If it is a misrepresentation then the results are useless when it comes to analysis.
Method /
Technique
Equipment used
Justification
Limitations
Vectored Pedestrian Flows
Paper, pen, stop watch
Vectored Pedestrian Flows are similar to Pedestrian flows but give a direction as well as a quantity. Useful for gauging where people are going
Because each area is being analysed for only twenty minutes, it must be trusted that the data is representational of the area. If it is a misrepresentation then the results are useless when it comes to analysis.
Comparative Land-Use Maps
Land-Use Maps of 1998 and 2004
Allows one to see the amount of retail change that has taken place since the opening of the Oracle. Required to gauge the effects that the Oracle has had on the lowest scoring zone
The maps for the years between 1998 and 2004 were unavailable so it is unsure what amount of activity took place then. The 2004 edition will be out of date in 6 months time making predictions difficult.
Chloropleth Shading Map
Map of lowest RQA scoring area, shading pencils
Gives a visual representation of the quality of an area. Dark areas indicate poor quality whilst light areas indicate high quality. An effective and quick method to see patterns of distribution and to locate particularly poor/high quality areas.
Dependant on accuracy of the RQA index scores and will therefore be as good as the sum of its parts, a poorly done RQA will lead to a misrepresentation of the data, any patterns found would therefore be invalid.
Scatter Graph measuring Pedestrian flow against RQA score
Data from pedestrian flow and RQA
Allows for relationships between the two independent variables to be statistically proven using various methods. Also allows for any obvious links to be seen
Dependant on the accuracy of the collected data.
Cross section map of lowest scoring area
RQA data and map of lowest scoring area
By dividing an area into ten districts of equal weight and plotting the results from the RQA score onto a graph one can immediately see the differential between districts. It then allows for close analysis of what makes the low scoring zones different from the others.
Dependant on the accuracy of the collected data. It is also easy to jump to the wrong conclusions when analysing the data. One must consider all possible options prior to making any conclusions.
Spearman's Rank Correlation Co-efficient
Scatter Graph measuring Pedestrian flow against RQA score, calculator
The Spearman's Rank Correlation Co-efficient is a statistical technique for measuring the correlation of two independent variables, in this instance it is used to measure RQA score against pedestrian flow. This is the most effective method for the type of data available.
It is easy to make mistakes with the calculations, as there are lots of numbers involved. The calculations should be double checked in order to ensure accuracy. Dependant on the accuracy of the collected data.
Risk Assessment
Whenever a study is conducted and data collection is required, there will be risks involved. However the chance of accidents occurring can be greatly reduced with forethought and correct preparation.
Following is a table containing a thorough list of potential safety concerns that may arise whilst data collection is taking place and suggestions for limiting the risks.
Risk
Probability of Risk Occurring
Level of Severity
Methods for Risk Limitation
Traffic Conflict
High
2-5
Heightened awareness near roads
Getting Lost
Low
5
Prior knowledge of area
Criminal activity (muggings etc)
Medium
5
Heightened awareness, avoid back alleys, stay near busy places
Personal Injury
Low
3
Appropriate footwear and an awareness of pavement conditions
Adverse effects of weather
Medium
2
Wear appropriate clothing
The precautions taken ensured that there were no incidents during data collection.
Hypothesis 1
This hypothesis will be focussed on identifying which of the three retailing district has the highest RQA index score and to identify whether high quality will attract more visitors.
In terms of predictions, one would expect to find that the Oracle, which is the newest of the three zones, would be of higher quality in all areas. This prediction can be made on the basis that since the 1990's and the creation of Out of Town Retail Parks, new inner city developments need to provide more than just shops, they need to have good quality materials and have a pleasant atmosphere.
The design and formulae for the RQA index can be found in the accompanying document entitled "RQA".
In order to identify which area has the highest RQA index score, the districts must be assessed in a blanket fashion (as discussed in the methodology) this is necessary to get an clear and accurate view of the whole district. With the data collected the most effective method for showing comparisons is a Bi-Polar graph.
Bi-Polar graph for RQA scores
This graph shows that there is no substantial difference between the three zones under analysis. It was predicted that the RQA scores for the Oracle would be significantly higher than the other zones with the High Street being the worst. Although the order in which the zones are ranked is as expected the differential is not. Since the Oracle is a new development it was predicted as having better facilities all round, but in the RQA index score it only comes first in two out of the six criteria, in one criteria it is beaten by the worst performer of the three areas. However, the graph is not completely unpredicted, the results for the Broad Street Mall were as expected, it under-performed compared with the Oracle but did substantially better than the High Street.
The first part of the hypothesis has been completed, what must be done now is to assess whether having a high quality development that has a high retail quality index will attract more visitors. In order to measure this, one must know the number of pedestrians entering the retailing zone, from which direction are they arriving and to where they are going. An assessment of pedestrian flows and directional pedestrian flows (known as vectored pedestrian flows) is the most effective method.
Pedestrian Flow diagram
The graph shows that there is a more or less equal balance of pedestrians moving into and out of the area. This is interesting since the data was collected between 10:00am and 11:00am when it would be expected that more people would be arriving than departing. The actual raw data is that (at this time) there are approximately 1109 people entering the zone every twenty minutes and approximately 934 exiting the zone every twenty minutes. This is an increase in the total population remaining in the zone of 19% that equates to an hourly increase of 875 people entering the zone. There is a fairly even distribution when it comes to precisely where people are entering the AUI with no one access route having significantly higher number of pedestrians passing through. Possible reasons for this are that Reading CBD has several focus points for the influx of visitors. It has two multi-story car parks within 200m of the High Street and the train station is approximately 300m away from the High Street. There are several routes that one can take to get from any of these locations, which accounts for the even distribution.
Vectored Traffic flow
This vectored traffic flow shows that the majority of pedestrians passing through the high street area are headed in the direction of the Oracle. The results are as predicted with the Oracle attracting a disproportionately higher number of visitors than the Broad street mall with a total of 2379 to 1658 (a difference of 721 which means that the Oracle is attracting 58% of the visitors) The graph also gives an indication of the sheer number of pedestrians that are passing through the area. It is difficult to draw analysis from this map as it is unsure how to categorise the last set of figures. By comparing the pedestrian flows through a sub-zone with the RQA scores for the sections of the high street we can see if there is a correlation. In order to assess this, a Spearman's rank correlation coefficient method is used (The formulae and full working can be found in the Appendices section). From this analysis, a Spearman's rank score of 0.13 is obtained. This would indicate that there is a positive correlation between RQA score and pedestrian flow however the correlation is not very strong. The closer a score is to 1.0 the stronger the correlation (a score of 1.0 represents a perfect positive correlation) a score of 0.0 represents no correlation, as you can see the link between pedestrian flow and RQA is rather weak.
From these results one can conclude that:
. The Oracle has the highest RQA index score of the three districts
2. The High Street has the lowest RQA index score of the three districts
3. The Oracle is attracting the majority of visitors
4. There is no one major access route through which most pedestrians are moving.
Detailed analysis of these conclusion points is given on the following pages:
Conclusions
. The Oracle has the highest RQA index score of the three districts
This conclusion is drawn from the fact that the Oracle produced an RQA index score of ZZZZZ compared with the Broad Street Mall's score of ZZZZZ and the High Street's score of ZZZZZ. The relative lack of differential could indicate one of two things: that the Oracle is not as good as at first thought or, that the other zones are developing to catch up with the Oracle. The problem that the Oracle faces is that it is of similar design to Out of Town Retail Parks, most notably to Blue Water where there are obvious comparisons in terms of both building design and shops available. However, the Oracle does not have the space to create the same atmosphere and as such does not live up to expectations. This is rather unfair because if we take the oracle as a stand-alone building it is designed and managed well. Of course, as will be investigated in Hypothesis 2, perhaps the reason for the limited differential is that the other two zones are being regenerated in an attempt to keep up with the Oracle.
2. The High Street has the lowest RQA index score of the three districts
More of a statement than a conclusion. This was to be expected. It is always difficult for High Streets to compete with retailing developments as they generally have a much larger focus and many different organisations looking after little bits, this makes cooperation difficult. In Reading, the local council is responsible for the maintenance and development of the actual pavement; the responsibilities also include the introduction of amenities (see Hypothesis 2). Whilst the owners of the individual shops are responsible for the maintenance and appearance of their properties. This situation does not exist in the Oracle where all shops have to have any changes / developments ratified by the Oracle's development team. In this way the Oracle's management team have overall control and can keep the quality constant. The problems faced with the High Street are outlined in Hypothesis 2.
3. The Oracle is attracting the majority of visitors
The data gathered from both the inflow and directional pedestrian flows give a clear indication that the Oracle is attracting a large percentage of people visiting the CBD. The direct result of this is that one would expect to see that other areas suffer as a result of this. In Reading this is not necessarily the case. Although it has been show n that the Oracle has a better retailing environment than either the Broad Street Mall or the High Street the aforementioned zones are not very far behind. What the inflow diagram has showed is that although eventually most people are headed towards the Oracle, they have to move through the High Street to get there, and as the Comparative Bar Chart of Pedestrian flows into the retail centres (found in the Appendices) there is still a large number of people entering the Broad Street Mall. In short one can conclude that despite the success of the Oracle, it has not (so far) led to the economic decline in the Broad Street Mall or the High Street.
4. There is no one major access route through which most pedestrians are moving.
As has been previously mentioned, the more or less even distribution (an average variance of 45 at each location). This is important because it indicates that every section of the High Street, the Oracle and the Broad Street Mall will get an equal number of visitors passing their doors. The connotations for which are that although the Oracle attracts the majority of visitors, the other two districts do get a fair share of visitors. Of course this conclusion only focuses on passing pedestrians and one must bear in mind that not every pedestrian will shop at a location.
What this hypothesis has shown is that quality, although important is not the only factor that determines the success of a development.
Hypothesis 2
The initial hypothesis focussed on determining a) a method for measuring retail quality and b) locating the best retailing area. This hypothesis is focusing on what the High Street can and is doing to improve itself.
The High Street generated the lowest score of the three retailing sectors and by a sizeable margin. In order to establish why this is so, there are several things that need to be done:
* Establish low scoring districts within the High Street
* Create a Visual representation of the High Street RQA (a chloropleth shading map) to ascertain whether the low scoring areas are nucleated
* Create a Land Use Map to establish whether there is an overwhelming majority of a type of shop
* Determine whether the location of amenities could be affecting the district scores.
These will allow for an analysis of what the shortcomings of the High Street are and to produce a scheme of appropriate action to help improve the situation.
The first thing that must be done is to create a cross section of the High Street showing the RQA category scores for each district, this will allow for weak areas to be identified.
High Street Cross Section
This cross sectional graph of the High Street area indicates that there is a trend between the proximity of a shop to a retail centre and their respective RQA scores. The peaks in sub-zone 3 (the district to the immediate right of the Oracle) and district 9 show this (the area across the road from the Broad Street Mall. However there are anomalies with this data. A possible reason for the low scores in districts 2 and 10 is that both of these districts have some exceptionally low RQA index scores (As shown in the chloropleth shading map), which will lower the overall scores. The photographs below give an indication of the low quality of some of these stores.
Chloropleth shading of the High Street
The chloropleth shading map shows that there are no clear zones of high quality / low quality within the High Street area. It does show that some of the largest chain stores such as Sainsbury's and Boots have comparatively lower scores than some of the smaller chain stores (such as Thornton's see photograph) and even independent retailers (such as the Ashley Bloom see photograph). This is contrary to what was expected. It was believed that because the Oracle has the highest RQA index score, the area surrounding the entrance would have higher scores due to the increased number of pedestrians that are attracted to the Oracle. It was also expected that shops near to the Broad Street Mall would benefit from the pedestrians visiting that location but not to the extent of the shops near the Oracle. The chloropleth shading shows that, in actual fact, the shop with the highest RQA score is the located furthest away from the Oracle (Laura Ashley). This would indicate that there is no relationship between the RQA score for a retail centre and the RQA scores for the surrounding shops. Continuing from this, by analysing where the activity is taking place we can determine which region needs to be improved. A way of doing this would be to calculate a sphere of influence from the Oracle.
Sphere of influence
The overlay diagram over the Changing Land Use Map shows the relationship between distancing from a retail centre and levels of economic activity. The graph shows that the majority of economic activity (39%) is occurring in the region that is the furthest distance from either the Oracle or the Broad Street Mall. The zone immediately adjacent to the Oracle has the lowest activity with 27% although most of these are new businesses opening. This can be linked with the results from the
Changing Land Use In the High Street
Based upon comparing the Land-Use Maps from 1998 and 2004. This graph shows the distribution of changing land use within the High Street. It has been divided into three sections indicating proximity to either the Oracle or the Broad Street Mall. It shows that the majority of activity is taking place in the area that is of equal distance from the two retail centres. This implies that the other two zones are benefiting from the quality of the retail centres.
When one regards the High Street cross section and compares it from the results of the sphere of influence map one can see that (excluding districts 2 and 9) the results found here coincide, albeit loosely. From this one can conclude that the problem is not specifically due to distancing alone.
A possible reason for the low quality of the High Street is that there are too many similar shops in a small location. If this were the case, then the shoppers would be more widely distributed than if there were fewer stores. If there are fewer customers then revenue will be less and there will be less money for improving the shop. A Land Use Map will give a visual representation of the distribution of shop types.
Land Use Map
Detailed analysis using pie charts to show distribution indicates that there is a wide variety of different shop types but there is no one particular type in significant abundance. What can be observed is that there is a nucleation of powerful department stores with a John Lewis, BHS and a Marks and Spencer within 50 meters of one another. This could be responsible for the poor quality of the surrounding zones. Because the variety of items available in a department store is so vast, it can ruin smaller businesses selling similar products, as customers are more likely to shop at the department stores. A more effective way of 'distributing the wealth' would have been to spread the department stores over the area. This would prevent surrounding shops from being totally starved of customers.
Nearest Neighbour Analysis of amenities:
There are two reasons why there are no graphs for the Oracle or the Broad Street Mall. They do not provide enough amenities to allow for a Nearest Neighbour Analysis to take place (a minimum of ten is required). So it is difficult to be able to directly compare the three zones. However this does allow for one to see that the council is doing to improve the High Street zone (the only zone in the investigation that is funded by the local authority). The Nearest Neighbour Analysis generated a score of 2.48 (for which formulae and working can be found in the appendices). This means that there is a specific structure in the way in which the amenities have been placed. This means that the council is thinking about where amenities are most needed rather than dispersing them evenly.
When the data gathered from the Nearest Neighbour Analysis is compared with the data collected from the High Street cross section one gets a very detailed idea of the High Street. The amenities in the High Street area are relatively new developments (last 5-6 years) and can be seen as an attempt by the council to encourage the prosperity of the district. The amenities have been chosen for very specific reasons. The multitudes of benches are the only ones available in the entire zone of inspection. This means that shoppers who do not want to purchase refreshment must come to the High Street to rest, during which time the shopper is likely to be window-shopping from his or her location.
For the purpose of analysis, the term 'amenity' is divided into three categories: High Order, Middle Order and Low Order examples of which are given below:
Order
Example
Score
High
Telephone boxes, covered shelters, plants/trees/hanging baskets, toilets
5 points
Middle
Benches, Street lights
3 points
Low
Litter receptacles, bike racks
point
Note: This investigation does not include local service amenities such as post boxes as this is not relevant for visitors.
The points system allows for each zone to be given a total score that combines the RQA index score with the amenities score.
If one were to look at the High Street zone overlay one would notice that there is a weak relationship between the number of amenities and the RQA index score. The relationship would indicate that the zones with the high RQA index scores have a higher number of (particularly High Order) amenities as is indicated by zone 3. It is debatable as to whether the concentration of amenities is a result of a zone having a high RQA or whether the concentration of amenities has lead to a high RQA. It would be logical that one would follow the latter proposition as the majority of the amenities in the High Street are seating facilities which, as mentioned earlier, allow visitors to window shop as they waited, it is sensible to assume that something in the vicinity would catch their attention.
Conclusions
From the data that has been collected, the following statements have been established:
. A weak correlation exists between RQA index score and distance from a shopping centre.
The relationship between RQA scores and distance from a retail centre is of important significance, as it implies that creating a retail centre such as the Oracle, will improve the quality of surrounding shops. The correlation is of significance because it has been proven by statistical analysis (using the Spearman's Rank Correlation Coefficient). The benefits of this knowledge are not directly applicable to Reading but have implications for other CBD's in towns and cities that are facing economic decline as a result of failing retail. By introducing a new retailing centre to the lowest quality area it will have a positive influence on the surrounding shops, thus improving the overall quality of the vicinity.
2. There is a detrimental knock-on effect if there is a nucleated cluster of prominent chain stores
Clustering powerful chain stores in one area will deprive the smaller chain stores and independent retailers of customers. This has not been proven statistically so cannot be verified but, by observation the relationship is apparent. The significance of this is that nucleation of prominent stores leads to the secular success of one specific zone whilst having a detrimental effect on the surrounding areas. This information would be of great importance to new developers specifically those trying to create a new High Street retailing district. In order to prevent this, a possible solution would be to limit the number of prominent stores (such as Marks and Spencer and John Lewis) in each section of the retailing area. By dispersing them, they will be an economic benefit (working on the same principle as creating a new retailing centre - see above) rather than as a negative influence.
3. The High Street is not generally of poor quality but there are several buildings that are lowering the overall standard.
This conclusion again is made not on statistical analysis but on observation. The chloropleth-shading map indicates that there are 4 or 5 extremely low scoring buildings that are have a negative effect on the overall quality of the High Street. Possible reasons for this would be that these low scoring buildings are independent retailers. However since this is not the case, there must be another reason for the poor quality. Some of the low scoring buildings are not low scoring because of display or atmosphere but on building materials. For example Sainsbury's moved into the building in the 1980's rather than having it custom built. Since there is very little that can be done with concrete clad blocks, the blame for the poor quality does not rest with them. However the display and lighting etc is there own fault. What is being suggested here is that the actual physical make up of the high street is of poor quality. What needs to be done is to have the high street renovated. The practicality of this situation is limited in that it would require companies to spend vast sums of money (that they might not necessarily have) to improve their shop fronts. Although this would have a benefit in beautifying the area and possibly attracting more visitors, some stores (such as Sainsbury's) have no competition in the Reading High Street, so would see no return from their development. A possible way to get round this would be for the local authorities to provide a subsidy or other such benefits such as tax relief. It would be in its own benefit for local government to implement schemes to improve the quality of the High Street.
4. The local authorities are attempting to improve the situation by adding amenities in the High Street.
Providing amenities for the convenience and is one of the critical things that can make a substantial difference. It is a tried and tested method for improving the shopping experience and one that is well used. But apparently not in retail centres...
Both the Oracle and the Broad Street Mall have little in the way of amenities whereas the High Street has copious amounts of them. The local authority is going about improving the High Street in exactly the right way. It is not only adding seating facilities, street lighting etc but it is utilising contemporary designs and high quality equipment. Because the High Street is the only shopping area that is providing these facilities, it would appear the local authorities are exploiting this benefit to the possible detriment of the shopping centres. For all the positives, the local authorities could improve the amenities situation. The distribution as indicated from the Nearest Neighbour Analysis shows some level of strategic placement, but what really needs to be done is have high order amenities installed in the low scoring areas of the High Street (zones 2 and 10). It would be foolish to just add more of the same, there are seating facilities and litter receptacles frequently along the length of the High Street, what is needed now is something unique. This would have two-fold benefits in that it would improve the quality of the district and attract additional customers. Possible amenities could be:
* Seasonal covered seating - in summer have parasols, stools and drinks holders in winter, have heaters and benches.
* Cover - marquee style tent covers
* Lockers - large lockers to store shopping, would need security
Concept sketches can be found in the Appendices
Other potential improvements could be water features or sculptures, although not strictly speaking amenities, it would make the area much more attractive.
Evaluation
The focus of this investigation was on the relationship that three retailing areas have on one another. The investigation has led to the creation of an index for measuring retailing environment quality, which as a stand alone piece is of much importance and has practical applications for developers and councils planning to regenerate retailing areas. It has also established which of the three retailing areas has the best retailing area and found statistical evidence to indicate that it does attract more visitors. It has also been established that the creation of a new retailing district may not have as much of a detrimental effect as would be expected. This is important because the research gathered indicates that in fact, the reverse is true, the creation of a retailing centre could potentially have a positive effect. This statement can be made because one can see that the other two districts appear to not be in decline, new shops are opening and the High Street is working hard to improve its facilities. It should be noted that the prior statements are strictly hypothetical; there is not enough data available to determine the quality of the districts 5 years ago. A repeat of the investigation in a decade or so would be required in order to validate the proposals.
Of course one must take into account the limitations of the methods (discussed in detail in the Methodology section) and the limited knowledge of local authority policies etc. much of the data was gathered over a period of twenty to thirty minutes, this is not really enough time to draw concrete conclusions, it does give a general consensus but it does mean that anomalous results can cause the data to be skewed. An example of this would be that during a later visit to the Oracle, a party of sixty or so Spanish tourists entered the shopping centre. Had pedestrian counts been being conducted; the data would have been misrepresentational. It is these kinds of things that one must be aware of. There was also a lack of repetition (known as scientific vigour) as time constraints limited when researchers were able to get on location. This means that one cannot be sure that the data was in fact representational. That said, the data did follow the expected results. Hypothesis one can be criticised for having a little bit too much faith in the quality of the Oracle - this fact has been discussed in the Conclusion section of Hypothesis 1. Hypothesis 2 can be criticised in that it is unclear as to the extent of funds available for improving the High Street and the amount of interest the local authorities have with improving it.
Overall the investigation has produced useful results that potentially have the ability to lead to increased prosperity of the High Street and of Reading itself.
APPENDICES
Nearest Neighbour Analysis: Formulae and Workings
NNI = 2 x ?(average) x ? (???)
NNI = 2 x 8.18 x ? (56/24000m2)
= 2.48
Spearman's Rank Correlation Co-efficient: Formula
?? ? (??d?)
References and Acknowledgments
Map of UK as found in the introduction section courtesy of:
www.sec-datacom.com
Map of Reading's CBD as found in the Introduction section, courtesy of:
www.reading.gov.uk
Background history as found in the Introduction section based on details given on:
www.reading.gov.uk
Map of M4 Corridor as found in the Introduction section, courtesy of:
www.aqa.org.uk
Spearman's Rank Correlation Co-efficient formula as found in Hypothesis 1 and the appendices, courtesy of the Mathematics department as St Johns School, Marlborough
Nearest Neighbour Analysis formula as found in Hypothesis 2 and the appendices courtesy of the Geography Department
Categories for the Land-Use Map as found in Hypothesis 2, courtesy of the Oracle Shopping Centre
Maps of Reading High Street as found in Hypothesis 1 and Hypothesis 2 courtesy of the Reading Public Library - many thanks to all staff for their help (especially with the photocopier...)
