The Measurement of Sub-Regional Industrial SpecializationAuthor(s): Stephen KennySource: Area, Vol. 9, No. 3 (1977), pp. 220-223Published by: The Royal Geographical Society (with the Institute of British Geographers)Stable URL: http://www.jstor.org/stable/20001241 .

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220 Systems analysis and mathematical models

Co-chairmen: Yu. G. Saushkin, Geograficheskii Fakul'tet, Moskovskii Gosudarst vennyi Universitet, Moscow 117 234, U.S.S.R. L. Curry, Department of Geography, University of Toronto, Toronto, Ontario, Canada.

Secretary: G. J. Papageorgiou, Department of Geography, McMaster University, Hamilton, Ontario, Canada.

Members: N. Alao, Department of Geography, University of Lagos, Lagos, Nigeria. G. P. Chapman, Department of Geography, University of Cambridge, Cambridge, England. Z. Chojnicki, Adam Mickiewicz University, Poznan, Poland. M. F. Dacey, Department of Geography, Northwestern University, Evanston, Illinois, U.S.A. 60201. S. Faissol, Fundacao Instituto Brasileiro de Geografia e Estatistica, IBGE, Av. Beira Mar 436, Rio de Janeiro, Brasil. T. Itoh, Institute of Geography, Mie University, 1515 Kamihama-Cho, Twu-City, Mie Prefecture, 514, Japan.

The measurement of sub-regional industrial specialization Stephen Kenny, Liverpool Polytechnic

Summary. Crop combination analysis is a very useful but surprisingly under-used geo graphical technique. The method is adapted here to measure spatial change through time using the Lancashire cotton industry as a case study and thereby showing that the classic pattern of geographical separation is an oversimplification.

Spatial variations in industrial activity have been the subject of much geo graphical research and the identification of areas of industrial specialization has often been achieved either by a subjective appraisal of distribution maps or by the application of more sophisticated statistical techniques. The latter can prove too complex when applied to a single industry where only a small number of variables are involved, and this is especially so in the field of historical geography where data sources are frequently restricted. However, geographers have developed a number of simple numerical models, of a type that permit real world situations to be compared statistically with abstract stereotypes. Though developed for an entirely different purpose, J. C. Weaver's crop combination technique1 is one of these; an analytical method which can be readily adapted to determine sub-regional variations, but which has been little used despite its utility and ease of calculation. The technique has previously been employed to identify multi-factor agricultural regions2 but it can be applied to many other situations and is particularly suited to the industrial context.3 The method used here is a minor modification of Weaver's technique, similar to that employed by Coppock and Thomas, which involves comparing a series of theoretical models with an observed situation.

The study of the distribution of cotton manufacturing in Lancashire during the last 50 years of the nineteenth century creates a need to identify areas of

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The measurement of sub-regional industrial specialization 221

specialization and provides a good example of the utility of this technique. During this period the Lancashire cotton industry underwent a remarkable

process of organizational and locational specialization. Manufacturing was carried out in three types of factory; specialized 'spinning mills', specialized weaving mills', and ' combined mills' in which both processes were found.

Fortunately, excellent data survive in the form of Worrall's Directory,4 which cites the precise location of each factory, its type and productive capacity. Thus, for each of 36 cotton manufacturing areas four variables are identified; the number of spindles in spinning mills, spindles in combined mills, looms in combined mills, and looms in weaving mills. The mapping and subjective assessment of the distribution pattern is possible but even with only four variables this becomes a difficult and unsatisfactory process, involving the visual comparison of the 144 elements, and some simplifying procedure is necessary.

The combination technique provides an objective means of analysing this pattern. First, a weighting factor is calculated to make the number of looms equivalent to the number of spindles, and four scores are obtained for each area. These data are then converted to percentages which are ranked and compared with a series of model situations. In an ideal ' one-branch' area the expected distribution would be 100% in one branch and 0%0 in the others, in a 'two branch ' area 50%0 would be found in the two branches and 0/ in the remainder, in the 'three-branch' situation the expected figures would be 33.3%0, 33.3%0 and 33.3%0 with 0%0 in the remainder, and so on until the number of model cases is equal to the number of variables. The observed and theoretical distribu tions are then compared using the least squares method: the deviations of each of the actual percentages from the model situation are calculated, these are then squared, summed, and divided by the number of variables. This process is repeated for each of the theoretical distributions and the one which has the lowest deviation score is that which most closely resembles the actual situation.

The resultant characteristic combinations can then be mapped and Figure 1A illustrates those for the Lancashire cotton industry in 1884. Although the pattern of local specialization and diversity is still complex, a number of sub regions emerge: 1. Regions of extreme specialization (one-branch combinations)

(a) spinning in specialized mills in Bolton and Oldham. (b) weaving in specialized mills in the smaller towns of north-east Lancashire.

2. Regions of specialization (two-branch combinations) (a) combined weaving and specialized weaving to the north and west of the

Rossendale Fells. (b) combined spinning and combined weaving in Rossendale and peripheral

towns. 3. Regions of diversity (three-branch combinations)

(a) weaving emphasis (CS-CW-W) in the extreme north. (b) spinning emphasis (S-CS-CW) in the Tame Valley and central Lanca

shire. 4. Regions of great diversity (four-branch combinations)-the large commercial centres of Manchester and Rochdale.

It is difficult to discern in Figure 1A (itself a simplification) anything as elementary as the classic twofold dichotomy between the spinning and weaving areas. In addition to the basic north-south division, specialization in both

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222 The measurement of sub-regional industrial specialization

spinning and weaving was generally greatest in the newer manufacturing centres, whereas the old ' combined' structure which dominated the industry in the mid-nineteenth century still survived on the periphery of the Lancashire textile region. Moreover, combined mills were generally the most important elements in the largest towns of the regions which displayed a greater diversity of processes (for example, Manchester, Preston, Blackburn and Rochdale). The specialist spinning centres of Oldham and Bolton were exceptions to this rule but here a long-standing tradition in cotton spinning was allied to local economies of concentration.

Thus the technique identifies quite complex spatial variations in industrial patterns but it perhaps proves to be the most useful in plotting the process of regional specialization through time. Figure 1B shows the combination indices for the Lancashire cotton industry in 1900 and illustrates the considerable changes that had taken place in the locational framework during the last 16 years of the century. These spatial developments were linked to a remarkable process of organizational specialization, which had transformed the industry from 1850 onward, whereby combined mills were displaced by specialized factories.5 The spatial consequences of these changes between 1884 and 1900 can be clearly discerned by comparison of the two maps. For example, special ization in weaving had transformed three towns in north-east Lancashire (Burnley, Accrington and Haslingden) into ' single-branch' weaving areas and the continued decline of the combined mill had changed the towns of Manchester and Heywood from ' regions of great diversity' into ' two-branch ' combina tions. In effect, these developments increased industrial specialization in the

weaving area of the north of the region and the predominantly spinning towns of south-east Lancashire. Thus, something more closely resembling the tradi tional dichotomy had emerged.

Despite its simplicity, this technique has been used little in comparison with other spatial statistics such as the location quotient. It provides an objective

A.1884 a one brarc dorninaryt B.1900

8 tw,o branch combirnatin

Cmve branch combination

Dfour branch combUination

S speoializeda sining

-: CS combined spinnrng * CW combined weaving

W specializee Stkvt r.

Source. Worrall's Directory, ()884 & 1900

0 10 S.~~~~~~~~~~~~~k

.. A Accrington He Heywood 81 Blackburn M Manchester Bo Bolton 0 Oldham

BuBurnley P Preston By Bury R Rochdale Ha Huslingdien S Stockport

Figure 1. Locational specialization in the Lancashire cotton industry, (A) 1884,

(B) 1 900.

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The measurement of sub-regional industrial specialization 223

clarification of complex patterns of industrial location and facilitates the

monitoring of spatial aspects of organizational change. Moreover, the method

is equally applicable to many other problems in historical geography where

change in regional organization through time is being studied. As the indices can be calculated for any number of ' crops ', ' industries ' or ' branches '

expressing a range from total specialization to complete diversity, the technique could also provide a useful means of analysis of land-use patterns and, possibly, social and employment patterns.

Notes 1. J. C. Weaver, 'Crop-combination regions in the Middle West', Geogrl Rev. 44 (1954),

175-200, and J. C. Weaver, 'Crop-combination regions for 1919 and 1929 in the Middle West', Geogrl Rev. 44 (1954), 560-72

2. J. T. Coppock, 'Crop, livestock, and enterprise combinations in England and Wales', Econ. Geogr. 40 (1964), 65-81, and D. Thomas, Agriculture in Wales during the Napoleonic Wars (Cardiff, 1963)

3. D. M. Smith, Industrial Britain: the North West (Newton Abbot, 1969), pp. 61-2 4. J. Worrall Ltd., The cotton spinners' and manufacturers' directory for Lancashire (Oldham),

available for most years from 1882 onward. 5. The number of combined mills fell from 436 in 1850 to 357 in 1890, while the number of

spinning mills increased from 517 to 596 and of weaving mills from 193 to 793. Factory Returns, 1850 and 1890.

Geography and Planning Working Group

A report of the working group's inaugural meeting held at the London School of Econo mics on 20 April 1977 to discuss the RTPI report on Planning and the Future.

This new working group has been formed in response to the enthusiasm shown at the Newcastle annual conference. It is intended to focus on policy issues in planning and their relationship to geography. The inaugural meeting, chaired by Peter Smith (Leicester Polytechnic), was held at the LSE on 20 April to debate the Royal Town Planning Institute's discussion paper on Planning and the Future. Sylvia Law, chairman of the working party which produced the report, and past president of the Royal Town Planning Institute outlined its proposals. In an era of change, planning must be all embracing and at the same time involved in the community. Consequently a new concept of planning service was required and a much stronger resource-based approach. Peter Hall (Reading), also a member of the working party, feared that the profound changes proposed would not be welcomed by related disciplines. He argued for a national resource planning agency and for an elite corps of planners on the French model. His centralist emphasis was challenged by Mike Clark of Swansea. There was a need for a more local approach to counteract the secrecy and concentra tion of knowledge in government. Cynicism and scepticism had replaced confidence and idealism in planning. If there was something wrong with planning why give it

more scope as the report argues? Andrew Blowers (Open University) felt the report's arguments for corporate and

community planning could result in considerable expansion of the planning service at a time of increasing public doubts about its social role. The corporate approach had foundered in many authorities, and planners were not necessarily the best equipped

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