The Clustering of Financial Services in London*



important) with an option of 0 if not applicable1. Factors are presented in total score rank
order which is simply the sum of recorded scores for a given factor. For example, a factor
which received 2 ranks of 1 (not important), 2 of 2 and 2 of 5 (very important) would
receive a total score of 2x1+2x2+2x5=16. This method could produce anomalous results
(e.g., a factor which receives some 1s and many 5s being ranked above one which has a lot
of 4s, no 1s but relatively few fives), but, after close inspection, does not appear to.

A useful benchmark for interpreting these total scores is the average (mean) of the total
score across all questions (where it was possible to compute a total score) which is 855.
This may be thought of as the score you would typically expect a factor to receive. The
95% confidence interval around this average is 808-901. Accordingly, a useful rule of
thumb in comparing the relative importance of each factor is that any total score below 808
is relatively unimportant and any total score above 901 is relatively important.

The heavy black lines divide factors into groups where there is no statistically
significant differences in the total score within groups but there is a statistically significant
difference between groups (based on the “conservative” sign test - see Appendix 2). This
indicates that factors within two heavy black lines were regarded as being of roughly equal
importance by respondents, but either side of a black line there is a difference in the degree
of importance attached to a factor.

Tests were conducted for the possible existence of statistically significant differences
in the scores among different
lines of activity (using contingency tables) and for significant
differences among
firms of different size (using the Kruskal-Wallis analysis of variance).
Such differences are commented on by exception where they are particularly strong and
interesting.

Two sets of analyses for differences by line of activity were performed. The first
looked at the three most frequently occurring lines of activity in the sample: banking, legal
services and insurance
2. These three comprise half the sample and for technical reasons
explained in Appendix 2 allowed the most fine-grained analysis to be performed. Other

1 The number of responses to many questions does not add up to 310 (the total number of questionnaires
returned), for the simple reason that some respondents did not answer every question.

2 In the questionnaire, each firm was allowed to rank up to three lines of activity in order of importance. The
analysis of the influence of line of activity is based only on number 1 rankings (see the figures in the boxes in



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