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Measuring innovation—applying the literature-based innovation output indicator to public services



Richard M. Walker , Emma Jeanes and Robert Rowlands



Department of City and Regional Planning Cardiff University Glamorgan Building King Edward VII Avenue Cardiff CF10 3WA Tel: 029 20875774 Fax: 029 20874640 E-mail: [email protected]


School of Business and Economics Exeter University Streatham Court Rennes Drive Exeter EX4 4PU Tel: 01392 264518 E-mail: [email protected] Correspondence to Dr Richard M Walker

Acknowledgement The research reported here has been funded by the Economic and Social Research Council’s Innovation Programme (Award L125251057) and the Housing Corporation. The views expressed here are those of the authors alone.


Measuring innovation—applying the literature-based innovation output indicator to public services

Abstract Governments have been encouraging public service organisations to innovate. However, little is known about the extent of innovation in public service organisations. A private sector approach to the measurement of innovation—the literature-based innovation output indicator (LBIOI)—is applied to public service organisations to address this significant information gap. The method is described and then explored in one public service sector English housing associations. A sample of 257 innovations is constructed and then subject to analysis. This initial testing of the LBIOI indicates that the approach can be applied across public services to create longitudinal data sets, which will enhance the communication of good practice and the use of evidence in public policy, management and research. This methodology is demonstrated to offer important insights to public service innovation and would allow important relationships to be explored, notably innovation and performance a relationship central to government’s promotion of innovation.


Measuring innovation—applying the literature-based innovation output indicator to public services



There has been a growing expectation by governments around the globe that public service organisations should and will innovate to enhance performance. In Britain this was seen by the emphasis placed upon market mechanisms and the use of non-state providers under the Conservative administration. The Labour administration have continued this theme, but promoted innovation through managerial and bureaucratic approaches, notably Best Value in local government, and through the work of the Cabinet Office. These expectations by governments highlight the political nature of innovation and the way in which public service organisations can use innovation to maintain organisational legitimacy: “…a public agency seeks to convince the public of its progressive and presumably efficient mode of operation” (Feller, 1981, p. 14). These factors reflect the subjective nature of innovation. They do not, however, undermine the importance of developing methodologies that allow the nature of public service innovation to be explored, particularly whilst little information exists about the extent of innovation in public service organisations, beyond occasional sectoral or country studies (e.g. Borins, 2000; Ferlie et al., 1984; Golden, 1990; Osborne 1998). There is, however, a longer pedigree of work on the innovativeness of the private sector. This work has typically assessed innovation through inputs measures such as, Research and Development expenditure, partial outputs such as patents or through primary survey work. The direct transfer of such approaches to the measurement of innovative activity is not always practical for public services, whilst the techniques themselves are problematic. During the 1980s and 1990s innovation output indicators were developed based upon secondary data sources. This method was developed in the USA and Europe (Edwards and Gordon, 1984; Kleinknecht, 1991) and more recently applied to the UK (Coombs et al., 1996). It seeks to address some of the measurement problems alluded to above to make modest claims about the pattern of public services innovation. The objective of this paper is to understand if Coombs et al.’s methodological approach, the literature-based innovation output indicator (LBIOI), can be applied to public service organisations and to assess its usefulness to public policy, management and research. The paper initially addresses issues of innovation measurement and classification. The method is then described. In Part III we report our research findings that undertook an initial test of the methodology in a public service organisation sector, that of housing associations or Registered Social Landlords and make some observations about the type of innovation and its origins. Conclusions indicate some methodological difficulties but demonstrate


the value of such an approach alongside other primary data collection techniques for public service organisations and their research.



Innovation is a complex concept. The organisational studies literature on innovation highlights a number of strands that need to be outlined prior to examining the classification and measurement of innovations. Innovation is a process, through which new ideas, objects and practices are created, developed or reinvented (Rogers, 1995; Kimberly, 1981). It relates to the introduction and application of ideas within a role, group or organisation (King, 1992). It is most commonly associated with processes, products or procedures, or outcomes (Abernathy et al., 1983). It is something new and novel to the relevant unit of adoption, rather than newness per se (Aitken and Hage, 1971; Hage and Dewar, 1973; Rogers, 1995), and therefore subjective. It is designed with the intent to benefit the individual, the group, organisation or wider society (Hosking and Morley, 1991; Anderson and King, 1991; Hosking and Anderson, 1992) though an innovation may have a negative and unanticipated impact (Osborne, 1998). Finally, and importantly, it is associated with discontinuous change (Tushman and Anderson, 1986; Tushman and Nadler, 1996; Osborne, 1998) and a process of destruction.

Innovation Classification In order to measure innovation and to be able to understand its magnitude it needs to be classified. The potential range and extent of different types of innovations and innovation research suggests that they may have many different attributes (Slappendel, 1996; Wolfe, 1994) and that measurement is problematic. Therefore Wolfe (1994) argues that it is important for researchers to specify the attributes of innovation as a starting point for understanding innovation. His review of innovation research identifies 17 attributes that can be used in the process of classifying and understanding innovations. Six of these attributes were found to influence innovation in previous research. These are adaptability, centrality, organisational focus, pervasiveness, radicalness and uncertainty (Wolfe, 1994, p. 419). However other researcher’s classifications have relied upon uni-dimensional categories or dichotomies (e.g. Damanpour and Evans, 1984; King and Anderson, 1995). By contrast Coombs et al. (1996) adopt a product focused definition of innovations (five of their six categories) in their literature-based innovation classification, in keeping with many of the private sector studies. The product focus can be problematic in the public sector where many innovations are service based, and where services are consumed at the point of their production (Normann, 1991). Within a public service context Osborne (1998) has developed a two dimensional typology of innovation in response to the traditional separation of innovation as product and process. The


separation of product and process in the innovation literature is related to organisation life cycles. New organisations are seen to produce product innovations whilst older, mature, organisations produce process innovations to enhance the technical efficiency of previous product innovations. However, such a perspective denies the possibility of ‘reinvention’ across organisational types or sectors or the impact of discontinuities. It is possible that organisations can ‘de-mature’ and move away from the ‘mature’ productivity/efficiency focus, to focus upon product development and diversity, which is implicitly assumed in government calls for public service innovation. Osborne’s (1998) typology combines the product and process separation allowing for product or process innovation to occur at any stage of the life cycle thereby highlighting discontinuity (innovation) and continuity (organisational development) along the dimensions of services and users, similar to those used by Ferlie et al. (1984) to describe innovations. Figure 1 presents this typology. The first dimension is concerned with the impact of organisational change upon the services that an agency produces, categorising them as existing or new ones, the latter involves ‘servicediscontinuity’. The second dimension is concerned with the relationship of an organisational change to the organisations users. Again it seeks to categorise the relationship to clients as meeting the needs of existing end-users groups, or new ones, which involves ‘end-user discontinuity’. This two dimensional typology leads to four types of innovation. First, total innovation, involving discontinuous change that is new to the organisation and serves a new user group. Second, expansionary innovation, where the change involves offering an existing service of the organisation to a new user group. Third, evolutionary innovation, where the change involves providing a new service to the existing user group of an organisation. Finally, developmental or incremental innovation (Bessant, 1998), where the services of an organisation to its existing user group are modified or improved. This typology of innovation is a useful classification mechanism that allows organisational change and development to be separated from innovation, be they total, expansionary or evolutionary. This approach to the classification of innovations will be used when we test the applicability of the LBIOI to public service organisations.


Innovation measurement and the Literature-Based Innovation Output Indicator. The promotion of innovation is a relatively new phenomenon for public service organisations. Consequently there is not a tradition of innovation research in the European context, which is, for example, reflected in the use of the term in the main academic journals where few articles are found in key journals such as Policy and Politics and Public Administration. It also means that there is no defined or generally accepted measurement approach. Techniques developed in the


1960s and 1970s, such as the Aston Measures, have been used by public service innovation authors such as Osborne (1998). However, these are measures of the structural characteristics of innovative organisations, a theme of research in its own right, rather than methods to discuss the characteristics of a sector. This paper, therefore, turns to private sector literature and models. A number of problems have been identified with existing measures in the private sector. First, measures of Research and Development activity indicate levels of input into the innovation development process not outputs. Furthermore there is not a tradition of large scale Research and Development in many public service sectors. Second, patents represent inventiveness or creativity and not innovation. They are also highly product focused and discretionary—innovations might not be patented. Third, surveys have been a more traditional approach in assessing the innovativeness or firms or the rate of adoption of innovations (Rogers, 1995; Wolfe, 1994). However, questionnaire surveys have their own methodological problems and are a burden to organisations. The bibliographic techniques of the literature-based innovation output indicator have been developed to discuss innovation in sectors of the economy. Coombs et al. (1996) application of this technique in the UK private sector uses technical journals as its information source and classifies the innovations. Their classified innovations are then descriptively compared to variables such as organisational size and innovation origin. The technique therefore moves away from inputs, measures of creativity and difficulties associated with questionnaire surveys. However, the use of LBIOI raises a number of issues for public services research. Though technical journals are plentiful there is not a tradition of carrying ‘new product announcements’ as there is in the private sector. Second social policy innovations are likely to be both product and process and the technique has previously been prone to capture product innovations (Coombs et al. 1996). Thirdly, the reporting of innovations in ‘technical’ or professional public sector journals is not necessarily independently controlled by an editor as it is for private sector journals. It is therefore reliant upon the reporting of innovation, which could reflect the self-marketing capacities of organisations. Notwithstanding these variations from the private sector model, data sources exist for innovation announcements in the public services. In particular the growth of good practice, often validated by professional agencies, regulators or government departments, is an important development and source of information in addition to professional journals. The model has a number of strengths. Critically the method does not burden public service organisations, unlike direct surveys or other techniques. It does not rely upon ‘snap-shot’ or one-off surveys and can be a continuous approach building longitudinal data sets and it can be used to track reported innovation over time to explore adoption and diffusion rates. The methodology can be comparative, between different public services and different countries. A number of weaknesses are also found in the model. These include the problems of judgement


over journal content. The possibility that some public service organisations will be better at generating announcements of their innovations than others or accessing funding opportunities for innovative work also needs to be recognised. In current (private sector) usage the model has been biased towards product and does not capture process innovations particularly well. However, by developing the breadth of the literature sources and adopting Osborne’s broader typology of innovation classification this problem can be addressed and the model applied to a range of human public servicesThe strengths of the model suggest it as a potentially useful technique. We now go on to outline the data sources and information for our exploratory application of the LBIOI and present results.



Data were collected for the period 1997-1999 for English housing associations. The data sources used were readily identifiable as the professional housing press (Agenda, Housing, Housing Today, Inside Housing). In addition to innovations reported in these publications, data were collected from the Housing Corporation’s Innovation and Good Practice Database that contains 817 entries. The Housing Corporation’s database contains information on innovation good practice, research projects and dissemination activities. Housing association in this data base were undertaking projects that were unlikely to develop without external support and had to produce results which could be generalised across the sector. Consequently, innovations had to be identified. Where insufficient information was available about either the innovation or the housing association the information was ignored. This led to a total database of 257 innovations. This was made up of 186 from the Housing Corporation databased and 71 from publications.

Information collection for database The information collected broadly followed Coombs et al. (1996) approach to characterise innovation in the sector. Information was collected on the following issues. Innovation description—the innovation was briefly described. Housing Association identity—the housing association responsible for bringing the innovation to the sector was identified and its name recorded. Type of innovation—the innovation was classified against Osborne’s typology. This part of the research is dependent upon the judgement of the individuals who are creating the database. To ensure consistency the research team independently classified the innovations and then compared their results. Discrepancies were discussed until a consensus was reached after reclassification (Coombs et al., 1996). Origin of the innovation—information about the national identity of the innovation was collected because context plays an important role in social policy innovations. For example, past policy importation has failed due to a lack of understanding of


context (see Clapham and Kintrea, 1987 for an example). Partnership innovation—the research by Coombs et al. (1996) noted that new or novel innovations were more likely to be found in joint ventures in their private sector research. In the housing association sector we have seen an emphasis upon interorganisational working and the emergence of a range of new interorganisational practices (Reid, 1999). Location of the innovation—the location of the innovation was noted to see if there were any geographical trends with some regions expressing a higher level of innovation. Housing association size—size as a determinant of organisational innovativeness is strongly debated. In the organisational innovation literature it is suggested that larger and mature organisations are more likely to produce productivity/efficiency innovations rather than new products and be less innovative per se (Kimberly and Evanisko, 1981). However, others have argued that size increases organisational slack creating the capacity for innovation (Berry, 1994). Two measures of size have been adopted. First, the absolute measure of the number of homes that RSLs owns and second, the stock: staff ratio to measure the intensity of the number of staff.

The data This section explores the innovations in the housing association sector to see if the technique provides useful data on the nature of innovation in a particular sector. Further, more detailed research would need to be undertaken to explain the innovativeness of organisations studied here or the processes which led to them being innovative. The results are presented under the following headings: type of innovation, origin of innovation and distribution of innovations across housing association sector. Table 1 illustrates the range of types of innovations using the Osborne typology. Nearly 60% of activities captured in our sample could be classified as major innovations—developing new services or serving new users. Of these the largest proportion developed services for existing users. A smaller proportion expanded their user base whilst 6% developed total innovations. To illustrate the type of innovations being developed an example of a total innovation was the movement of associations into private renting where they served different users and had to develop new services. Expansionary innovations were often associated with stock transfers and various forms of formal and informal alliances between associations. Evolutionary innovations were seen in the development of new community services to housing association tenants and development or incremental innovations focused upon organisational development and training. It would be expected that for any sector there would be more developmental activity than other types because these are less risky developments seeking efficiency to known processes or products, and known end users. It could also be argued that a public service


organisation would be more likely to innovate to provide new products or processes to known end users rather than expanding to provide to new end users, given their nature and purpose. The origin of the innovation, between domestic and international is shown in table 2. The table illustrates the dominance of the domestic context for these ideas, which can be explained by the relatively parochial nature of housing associations in the international sector. Table 3 indicates that nearly half of the innovations were undertaken by a single housing association, rather than in partnership with other housing associations or other organisations. Partnerships were more likely to be with organisations other than housing associations, and included local authorities, consultants and a range of other private sector organisations. The distribution of innovations by stock size, staffing ratio and their government region are discussed in tables 4, 5, and 6 respectively. The majority of the innovations reported were based in the mid-range of housing association (stock units between 250-5000) with very few in the smallest associations. Table 5 indicates that those who have the highest staff: stock ratios are not the main innovators, but those with the smaller staff stock ratios account for 67% of the innovations reported. There is an uneven spread of reported innovations; in particular, nearly a third of all those reported were based in London (table 6). This may be partly explained by the greater number of associations in the region. The innovation index in table 6 reveals that whilst London remains the most innovative region, the propensity to innovate is high in both the North and West Midlands regions. We now go on to tabulate partnership, size, stock: staff ratio and region against the type of innovation. The limited number of international originated innovations makes any inferences in table 2 limited. That the international origins may have produced a disproportionate number of total innovations to what may have been expected (14% as against 6%) seems intuitively reasonable (less ambitious innovations are probably developed or identified more locally), but the numbers are too small to make any strong inferences. Table 7 indicates that the total innovations were disproportionately sole rather than partnership activity, although the expansionary and to a lesser extent evolutionary innovations were disproportionately partnership activities (with other housing associations and non-housing associations respectively). The developmental activities were also disproportionately sole activities rather than in partnership with non-housing associations. These findings therefore lend some support to Coombs et al. study, and where it differs, in the case of total innovations, the numbers are relatively small. However, the results are not statistically significant. As discussed before, the small number of total innovations means conclusions cannot be drawn from table 8, however the findings imply that the more efficient types of housing associations are those who produce total innovations. Both evolutionary and developmental innovations, the 1-2.5, and 5-10 staff stock ratio categories have disproportionately more innovations identified. The evolutionary innovations also produce mixed findings with the 10-15


category of staff: stock ratio being disproportionately innovative in this category. It is therefore difficult to conclude any progression of efficiency or slack as an indicator of the type of innovations produced. Table 9 produces significant results to indicate that larger housing associations produce more total innovations and a high level of developmental activity. Expansionary innovations were more prevalent amongst the smaller associations and medium sized associations were more likely to undertake evolutionary activities. A high number of non- housing association led innovations were total suggesting the use of these organisations for their diverse skills and expertise. Table 10 illustrates the regional variations in the types of innovative activity, but is not significant. London originates half the total innovations whilst the Eastern and South West regions produce disproportionately more total innovations than might be expected. Our analysis has provided some evidence about the pattern of innovation in the housing association sector whilst raising some questions for additional investigation. The main feature of the results presented above is the emphasis by housing associations upon evolutionary innovation or developmental activity to provide services to existing user-groups. Total innovation is limited in the housing association sector. However, this finding concurs with Coombs et al.’s work on private sector organisations (which suggest that 8% of reported innovation approximate to ‘total’ innovations) and Osborne’s (1998) work on the personal social services. Where results were significant they were concerned with the issue of organisational size and the propensity to innovate which is debated within the innovation studies literature. The findings of this work suggest that nearly all innovations take place in medium and large housing associations and disproportionately amongst the larger (over 5,000 homes). Two areas for additional investigation are highlighted, first, the regional variation of innovation. The Eastern region’s innovative activity appears disproportionately ‘total’ or ‘evolutionary’ (both involving new products) whereas the East Midlands is disproportionately involved in expansionary innovative activity. Where the total numbers of innovations are larger (North-West, West Midlands, South-East & London) less variations are noticeable. Only the South-East appears to deviate much from what is expected through little involvement with total innovations, but a focus on evolutionary innovation. Where the regions are similar is in the proportion of developmental activity, roughly 40% of activity, bar one region. This question needs to be addressed through primary research on the characteristics of innovative organisation, concerning the significance of variables such as professionalism, specialisation, functional differentiation and slack (Damanpour, 1991).Second, the tendency for associations to work alone on the more ambitious innovations could be explored in light of the increasingly competitive environment. Issues of organisational skills could explored for the predominantly housing association partnerships seen in relation to expansionary innovations (addressing new potential customers) and the non-housing association partnerships for new


products. This would require the use of a different set of innovation theory, this time concerned with the process of managing innovation (Van der Ven et al., 1999). Here in-depth studies in organisations would seek to understand the processes of innovation initiation, development and implementation.



The exploration of the LBIOI methodology indicates that it can play a role in public services research and management. It has been adapted to the public services sector by adopting Osborne’s innovation typology to classify innovation. This provides a clearer picture of nonproduct based innovation and enhances the classification system adopted by Coombs et al. (1996) in their private sector study and means that it has usage amongst all human services. Its usefulness as a research methodology and tool to describe innovation in a sector has been illustrated in our exploratory study of housing associations. This suggests that the technique ‘captures’ data that have some validity and reliability and that it can play a role in public services management and research. There are however, a number of methodological issues that need to be recognised. In particular, the sources of literature used in studies would need to be fully described to be clear about the use of reported innovations and to recognise the conspicuous use of innovation by public service organisations. Furthermore, this approach is not a substitute for primary research data on public service innovation—it can compliment or supplement them—to provide modest databases. However, at a time when public service organisations are ever increasingly researched, bibliographic approaches provide an alternative approach to data collection to build pictures of innovation activity in sectors. Critically, its main advantage is that it does not burden organisations with questionnaire completion. Being a technique to describe the nature of innovation in a sector, and not just describe the innovation (e.g. Ferlie et al., 1984) it advances other work in this field. However, research on why some organisations are more innovative than others, the structural characteristics of innovators using the Aston measures, or the ways in which these organisations manage and develop innovation would require additional primary research, because they are associated with different innovation research perspectives. Bearing these issues in mind the approach could usefully be extended to other areas of public services to establish wider databases, longitudinal studies of innovation and to make comparisons between different sectors. The establishment of such data sets would also make it possible to begin to explore the relationship between innovation and performance in public service organisations and to track changes in the nature of innovations developed by public service


organisations and the context within which they work. This would aid government and public service managers in their decision-making and wider public services innovation research.


References Aitken, M. And Hage, J. (1971) The organic organization and innovation. Sociology 5, 1, pp63-82 Anderson, N. R. And King, N. (1991) Managing innovation in organizations. Leadership and Organizational Development Journal, 12, 1, pp. 17-21 Berry, F. S. (1994) Innovation in public management: the adoption of strategic planning. Public Administration Review 54, 4, pp. 322-329 Bessant, J. (1998) ‘Developing continuous improvement capability’ International Journal of Innovation Management 2, 4, pp. 409-429 Borins, S. (2000) What border? Public management innovation in the United States and Canada, Journal of Policy Analysis and Management 19, 1, pp. 46-74 Clapham, D. and Kintrea, K. (1987) Importing housing policy: housing co-operatives in Britain and Scandinavia. Housing Studies 2, 3, pp. 157-69 Coombs, R., Narandren, P. and Richards, A. (1996) A literature-based innovation output indicator. Research Policy 25, pp. 403-13 Damanpour, F. (1991) Organizational innovation: a meta analysis of effects of determinants and moderators. Academy of Management Journal 34, pp. 555-90 Damanpour, F. And Evan, W. M. (1984) Organizational innovation and performance: the problem of “organisational lag”. Administrative Science Quarterly 29 pp. 392-409 Edwards, K. L. and Gordon, T. J. (1984) Characterisation of innovations introduced on the US market since 1982. (Futures Group, Glastonbury, Connecticut, US) Feller, I. (1981) Public-sector innovation as “conspicuous production”, Policy Analysis 7, 1, pp. 120 Ferlie, E., Challis, D. and Davies, B. (1984) Models of innovation in the social care of the elderly, Local Government Studies 10, 6, pp. 67-82 Golden, O. (1990) Innovation in public sector human service programs: the implications of innovation by “groping along”, Journal of Policy Analysis and Management 9, 2, pp.219-248 Hage, J. And Dewar, R. (1973) Elite values versus organizational structure in predicting innovation. Administrative Science Quarterly 18, pp. 279-290 Hosking, D. M. And Anderson, N. R. eds. (1992) Organizational Change and Innovation: Psychological Perspectives and Practices in Europe. (Routledge, London) Hosking, D. M. And Morley, I. (1991) A Social Psychology of Organizing, (Harvester Wheatsheaf, London) Kimberly, J. R. And Evanisko, M. J. (1981) Organizational innovation: the influence of individual, organizational and contextual factors on hospitals adoption of technological and administrative innovations. Academy of Management Journal, 24, pp. 689-713 King, N. (1992) Modelling the innovation process: an empirical comparison of approaches. Journal of Occupational and Organizational Psychology, 65, pp. 89-100 King, N. And Anderson, N. R. (1995) Innovation and Change in Organizations. (Routledge, London) Kleinknecht, A. (1991) Towards literature-based innovation indicators. (SEO, Amsterdam) Normann, R. (1991) Service Management. (John Wiley, Chichester) Osborne, S. P. (1998) Voluntary Organisations and Innovation in Public Services. (Routledge, London) Reid, B. (1999) Reframing the delivery of local housing services: networks and the new competition. in G. Stoker (ed.) The New Management of British Local Governance. (Macmillan, Basingstoke) Rogers, E. (1995) Diffusion of Innovations. (Free Press, New York) Slappendel, C. (1996) Perspectives on innovation in organizations. Organization Studies 17, 1, pp. 107-129 Tushman, M. L. And Anderson, P. (1986) Technological discontinuities and organisational environments. Administrative Science Quarterly 31, pp. 439-465


Tushman, M. L. And Nadler, D. (1996) Organizing for innovation. In K. Starkey (ed.) How Organizations Learn. (International Thompson Business Press, London)

Van de Ven, A., Polley, D. E., Garud, R. and Venkataraman, S. (1999) The Innovation Journey New York: Oxford University Press. Wolfe, A. (1994) Organisational innovation: review, critique and suggested research directions. Journal of Management Studies 31, 3, pp. 405-431


Figure 1:

A typology of public services innovation USERS New


Total innovation






Source: Osborne (1998)

Table 1 Type of innovation Innovation classification

Number of innovations


Total Expansionary Evolutionary Developmental

16 31 104 106

6 12 41 41




Number of housing associations


Domestic International

250 7

97 3




Table 2 Geographical origin of innovation Origin of Innovation


Table 3

Partnership origin of innovation Number of housing associations


One RSL alone Partnership with other RSLs Partnership with other organisations

121 54 77

47 21 30




Table 4

Distribution of innovations by stock size

Size of HA (By Stock)

Number of housing associations


> 5000 250 – 5000 5000

250 to 5000

Non housing association

< 250

Total Expansionary Evolutionary Developmental

6.7% 9.3% 38.7% 45.3%

4.3% 12.9% 43.1% 39.7%

0% 16.7% 33.3% 50.0%

10.7% 14.3% 35.7% 39.3%







Chi = 4.370, p = 0.976 Table 10

Innovation type by region

Classification of Innovation


North West

Yorkshire & Humberside

West Midlands

East Midlands


South West

South East


Total Expansionary Evolutionary Developmental

5.9% 5.9% 47.1% 41.2%

0% 13.2% 42.1% 44.7%

6.3% 6.3% 37.5% 50.0%

5.9% 11.8% 38.2% 44.1%

0% 50.0% 25.0% 25.0%

12.5% 0% 50.0% 37.5%

12.5% 18.8% 31.3% 37.5%

2.9% 8.8% 47.1% 41.2%

9.8% 11.6% 39.5% 39.5%












Chi = 21.516, p = 0.608


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