History Matters: Path dependence and innovation in British city ...

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Map 2: Introduction of novel products in GB cities CIS4, 2002-2004 Figures have been based on indexes Great Britain = 100 Percentage as index number > 137 Top 116 to 136 100 to 115 90 to 99 75 to 89 < 74 Bottom Unsampled data Mean 101.72 Standard Deviation 31.86 Miles Kilometres 0 25 50 0 25 50 75 100 Source: Travel-to-Work Areas 1998. National Statistics. 22
2.2 Selection of leading and lagging city-regions In order to select particular cities to illustrate the nature of path dependent development and the respective roles of their collective absorptive capacities and local innovation systems in their development, we first analysed the innovation outcomes shown in the results of CIS4 for all 63 British cities with core populations greater than 125,000. Figure 10 shows the introduction of novel products between 2002 and 2004 and the wide variation in innovation outcomes between British cities. The highest rates of such innovation were located mainly in Southern England particularly around the Greater South East (GSE). The lowest rates were disproportionately concentrated in cities located around peripheral coastal areas in England and Wales and also in middle and Northern England. In order to illustrate the historical trajectories that have led to such results we selected a sample of 12 cities for further more detailed analyses using existing data sets (mainly time series). Six were selected from the top deciles of performers on the six different measures of innovation outcome provided by CIS4. A further six were selected from the corresponding bottom deciles. Table 1 shows the results of this selection exercise. 2.3 Path dependent development in old and new industrial areas is diverging From our selection of cities, we can see the long-term nature of the pathways followed to arrive at their positions in the early 21st century. Thus, all the cities in the lowest deciles except Norwich had experienced rapid Table 1: Best and worst performing cities on CIS4 innovation measures Innovation measure Cities in top decile (best first) Cities in bottom decile (worst first) Percentage of firms introducing novel products Percentage of firms introducing novel processes Percentage of firms introducing new or improved products Percentage of firms introducing new or improved processes Percentage of firms implementing major changes to organisational structure Percentage of firms implementing changes in marketing concepts or strategies Cambridge (35 per cent) Aldershot (27 per cent) Northampton (25 per cent) Portsmouth (23 per cent) Northampton (11 per cent) Wakefield (11 per cent) Cambridge (10 per cent) Bournemouth (9 per cent) Cambridge (45 per cent) Northampton (42 per cent) Aldershot (38 per cent) Milton Keynes (38 per cent) Oxford (32 per cent) Northampton (29 per cent) Southampton (27 per cent) Bournemouth (26 per cent) Reading (34 per cent) Milton Keynes (31 per cent) Portsmouth (31 per cent) Oxford (31 per cent) Warrington (32 per cent) Reading (31 per cent) Birkenhead (31 per cent) Crawley (31 per cent) Swansea (6 per cent) Leeds (10 per cent) Birkenhead (11 per cent) Cardiff (11 per cent) Newport (2 per cent) Southend (3 per cent) Mansfield (3 per cent) Leeds (3 per cent) Swansea (18 per cent) Norwich (20 per cent) Southend (22 per cent) Cardiff (24 per cent) Leeds (13 per cent) Norwich (15 per cent) Stoke (16 per cent) Swansea (16 per cent) Wakefield (13 per cent) Preston (16 per cent) Newport (16 per cent) Southend (17 per cent) Wakefield (13 per cent) Middlesbrough (15 per cent) Swansea (16 per cent) Norwich (16 per cent) Source: Analysis of CIS4 dataset at city level, for GB cities with a population above 125,000 and a sample size of at least 75 firms in CIS4. Cities highlighted in bold are those included in the final selection of 12 cities. 23
Page 1: Research report: July 2008 History
Page 4 and 5: Executive summary History matters:
Page 6 and 7: 5. Strong local social networks. By
Page 8 and 9: Acknowledgements This report was wr
Page 10 and 11: Part 1: Introduction 1.1 History ma
Page 12 and 13: Figure 2: Three perspectives on eco
Page 14 and 15: Figure 4: Two alternative path depe
Page 16 and 17: In the long-run, city-regional econ
Page 18 and 19: into new practical and commercial f
Page 20 and 21: Part 2: Path dependence and innovat
Page 24 and 25: Figure 8: Selected cities best fit
Page 26 and 27: Figure 10: Change in knowledge-inte
Page 28 and 29: Figure 12: Knowledge partners locat
Page 30 and 31: Figure 14: Change in proportions of
Page 32 and 33: Figure 15: New firm formation in se
Page 34 and 35: Figure 17: New firm formation by in
Page 36 and 37: Part 3: Cambridge and Swansea: cont
Page 38 and 39: Around the same time, the public se
Page 40 and 41: with around 10-12 firms on each of
Page 42 and 43: Figure 19: The growth of high-tech
Page 44 and 45: Figure 22: Cambridge annual employm
Page 46 and 47: Figure 24: Cambridge and Swansea em
Page 48 and 49: Figure 25: Cambridge and Swansea kn
Page 50 and 51: Figure 27: The explosion of patenti
Page 52 and 53: Figure 29: Cambridge and Swansea na
Page 54 and 55: average in all forms of innovation
Page 56 and 57: Figure 32: Cambridge and Swansea na
Page 58 and 59: new technologies, products or proce
Page 60 and 61: innovation. The Cambridge cluster w
Page 62 and 63: Part 4: Why do cities differ in inn
Page 64 and 65: of the subsequent construction of s
Page 66 and 67: These two studies illustrate how qu
Page 68 and 69: 68 or technology transfer programme
Page 70 and 71: Map 4: Warrington Master Plan 1972
Page 72 and 73:
Map 6: Analysis of innovation outco
Page 74 and 75:
Map 8: Analysis of innovation outco
Page 76 and 77:
Map 10: Analysis of innovation outc
Page 78 and 79:
Map 12: Analysis of innovation outc
Page 80 and 81:
Appendix 2: Secondary data indicato
Page 82 and 83:
Indicators of path dependent develo
Page 84 and 85:
Table 11: GVA per capita Indicator
Page 86 and 87:
Table 17: Patent applications per c
Page 88 and 89:
Table 22: Geography of knowledge ne
Page 90 and 91:
Table 28: Occupational breakdown of
Page 92 and 93:
Cohen, W. and Levinthal, D. A. (199
Page 94:
Roberts, M. (2004) The Growth Perfo
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