Let me now describe the data available on the number of companies. I have created three categories: independents, C-Ss and Other C-Ss. The C-Ss are divided in two sub-categories, large and small scale C-Ss (the last one is named Other C-Ss). The largest firms which are included in the C-Ss category are Starbucks, Costa Coffee, Coffee Republic and Caffe Nero. The sub-category of C-Ss with a smaller scale of Chain-Stores (more than 1 coffee shop but less than 10 in Central London) consists of more than 20 firms. Notice that the four largest C-Ss had a minimum of 30 coffee shops in Central London. Hence, changing the upper bound of the Other C-Ss (which was set at 10) will not have any impact on the categorization of the C-Ss, if the criterion is less than three times the present value of the upper bound. The lower bound was chosen to be 2 stores in order to identify the non-strategic fringe (the importance of identifying a non-strategic fringe has been explained in the theoretical chapter of this topic)
3http://batchgeo.com/
of coffee shops which were named as independents. I have decided to decompose the C-Ss into two subgroups because I believe that the smaller C-Ss might be more aggressively competing with the independents than the major C-Ss. In other words, the major C-Ss leave no space for their individual stores (within Central London) to adjust their product availability or pricing in different sub-markets, while I feel that this might not be the case for the smaller C-Ss (which have more freedom at individual store level). Some examples of small C-Ss are Aroma, Seattle Coffee Co, Baggelmania, Apostrophe, Manhattan Coffee Co. and AMT.
As for the independents, it was found in the data that the independents are quite heterogeneous with respect to their operations. Four different subcategories of independent coffee shops were identified; patisseries, sandwich bars, delicatessens and coffee shops. The larger in size subcategory are coffee shops, the second in size are sandwich bars and the smaller one (less than 100 firms) are patisseries and delicatessens5. In the empirical analysis I do not
separate the different subcategories of independent coffee shops.
As for the major C-Ss, Starbucks is the largest operator with more than 100 coffee shops in Central London. In 2003 Starbucks had begun a worldwide acquisition of Seattle Coffee Co which was completed by 2003. As a result the number of Starbucks stores exogenously increased dramatically within a year; approximately 40 new shops were opened just in Central London6. With the exception of that year, Starbucks had a small number of coffee shops
opened in Central London afterwards, approximately 5 per year. The second largest player, Costa Coffee, had mild entry behavior with 2-3 new stores opening each year in Central London. Moreover, Caff´e Nero had acquired Aroma in 2002, which generated a similar jump of the number of new C-Ss but afterwards Caff´e Nero had 1-2 stores opened every year. Additionally, it seems that Coffee Republic with approximately 30 coffee shops in Central
5I realize that the subcategories are observed with a measurement error since in most cases the name of
the coffee shop does not reveal its operations and a coffee shop might have chosen to be listed as a coffee shop rather than another subcategory.
Figure 3.1: Number of Coffee Shops and Subgroups Market Shares
London has been a minor player in the industry, with minimum entry and mainly exiting the market.
The total entry of the C-Ss corresponds to 23% of all entry, the other C-Ss category corresponds to 18% and the independents to 59%. The average number of C-Ss per market is 3.91, which corresponds to 23% of the market. The average for other C-Ss is 2.73, which corresponds to 16% and for the independents is 10.6 which corresponds to 62% of the mar- ket. This means that the bulk of entry comes from the independents and suggests that the independents are not displaced or deterred by the C-Ss (since the independents keep entering the market and they are preserving their large share of the market). The graph (3.1) presents the market size and the market structure of the industry.
The graphs where constructed by taking the average cross-sectional value per market7
and plotted across the years available. In graph3.1we can see that the number of coffee shops remains relatively unchanged across time, with the only exemption being the years prior to 2003. Most importantly, the right hand side graph suggests that the C-Ss fail to dominate the market. This can be seen at the right hand side graph of figure 3.1 where the C-Ss enjoy a small share of the market and it is relatively unchanged across time; the latter holds across all groups as well. Interestingly, the graphs in figure 3.1 show that the industry is overall
Figure 3.2: Total Entries and Exits
relatively stable (satiated) and this holds either overall or within groups. However, notice that within markets it is observed that there are both increasing and decreasing numbers of coffee shops across time.
Figure 3.3: Entries and Exits by Subgroups Market Shares
The second group of graphs (figure3.2 and figure3.3) present a similar case as with the first group. The total entries are approximately equal to the total exits (on average across all years). It is also worthwhile to mention that there are cases where exits are larger than entries within the sample, thus a lot of variation both on entry and exit, but on average it seems that they cancel out each other. The graphs of the second figure (figure 3.3) show that both entry and exit are dominated by the independents. The smallest exit rate belongs to the major C-Ss, the minor (other) C-Ss have approximately the same entry and exit rate. Most importantly, the entry rate of the independents is higher than their exit rate, suggesting
that the independents are not being displaced or deterred to enter the market by the C-Ss. Another notable result is the entry of the C-Ss in 2003 where there is a jump. This jump is attributed to the Starbucks acquisition of Seattle Coffee Co. Furthermore, it seems that this aggressive entry had an impact on the group of C-Ss rather on the other groups since the C-Ss had the smallest growth after 2003. The exit rates are influenced by 2003 as well. This can be seen in the right hand side of the last group of graphs in figure 3.3. In 2003 there is a jump on the number of exits for both the independents and the major C-Ss. On average there are 1.77 exits per year per tube station with 13% (or 0.23 per year per station), attributed to the Chain Stores, 21% (or 0.37 per year per station) to the minor (other) C-Ss and 66% (or 1.17 per year per station) to the independents. On total there are 18 firms per market in a year (see the 3.2 graph), on average, with 2 entries per tube station per year and 1.78 exits. More than 50% of these entries and exits are attributed to the independents. The C-Ss, both major and minor, have a smaller presence in the market and smaller entry and exit. Summary statistics are provided in the appendix.
In the following graphs I abstract from time variation and focus on cross-sectional vari- ation8. The 3rd set of graphs (see figure 3.4) present the number of firms per tube station
and the number of the subgroups with respect to the Totaltube9 variable.
The left hand side graph, of the 3.4 figure, suggests that as the traffic of a tube station increases (more people are visiting it) the number of coffee shops that can be supported increases. However, it seems that from a point and afterwards it is inconclusive, for log values of tube traffic greater than 9. This suggests that in tube stations with high traffic there are other factors that influence the number of firms; strategic interactions might be one of them or other market characteristics. As for the right hand side graph, it seems that the previous finding holds within subgroups as well. The number of coffee shops, within
8Hence, each observation corresponds to a tube station with the variables being averaged across time. 9The total number of people that visit the tube station, averaged across time.
Figure 3.4: Total Firms and Subgroups to Totaltube
subgroups, increases as the traffic increases up to a point and afterwards is inconclusive. A possible explanation to that finding is that higher traffic areas can sustain a larger number of coffee shops but from a point and afterwards this is not necessarily the case as it seems that other forces come in to play. Furthermore, the number of independents seems to remain high (relative to the other subgroups) irrespectively of the traffic of the tube station. The failure of the C-Ss to displace the independents can be attributed by the existence of product differentiation and/or a focus of the C-Ss to within their group competition. Finally, in the appendix I also provide a set of graphs that present the number of firms and its decomposition into the subgroups with respect to the geographic size of the area.