The Creative Industries, Creative Occupations and ...

European Planning Studies

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The Creative Industries, Creative Occupations and Innovation in London Neil Lee & Emma Drever To cite this article: Neil Lee & Emma Drever (2013) The Creative Industries, Creative Occupations and Innovation in London, European Planning Studies, 21:12, 1977-1997, DOI: 10.1080/09654313.2012.722969 To link to this article: http://dx.doi.org/10.1080/09654313.2012.722969

Published online: 25 Sep 2012.

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European Planning Studies, 2013 Vol. 21, No. 12, 1977–1997, http://dx.doi.org/10.1080/09654313.2012.722969

The Creative Industries, Creative Occupations and Innovation in London

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NEIL LEE∗ & EMMA DREVER∗∗ ∗ Department of Economics, Lancaster University Management School and The Work Foundation, London, UK, ∗∗ National Centre for Social Research, London, UK

(Received November 2011; accepted June 2012)

ABSTRACT London is a global hub of the creative industries. These industries are seen as both innovative in themselves and an input in innovation processes in other sectors. Yet few studies have tested these relationships. This article investigates these issues using large-scale survey data for London. Using four measures of product and process innovation, we find no evidence that London’s creative industries are more innovative than other sectors. Yet, individuals doing creative occupations in other sectors are a robust driver of product innovation in London’s firms. The results suggest that occupations performed in London may be an important driver of product innovation in the city, and firms in other sectors may use creative occupations to develop new products in the capital. This finding is supportive of policies attempting to stimulate the creative industries by integrating creative occupations into firms across the whole economy.

Introduction London is one of the dominant cities in the world economy and a key city for the production of cultural goods (Pratt, 2006, 2009; Sunley et al., 2008; Comunian, 2011). The creative industries are defined by the UK government Department for Culture, Media and Sport (DCMS) as those which “have their origin in individual creativity, skill and talent and which have a potential for wealth and job creation through the generation and exploitation of intellectual property” (Department for Culture, Media and Sport, 2010, p. 4).1 They are an important part of London’s economy. Freeman (2010) estimates that in 2007 around 386,000 people were employed in London’s creative industries, more than were employed in financial services. If creative occupations are included, the figure is far higher: an additional 411,000 people worked in creative occupations in non-creative industries. The creative industries and creative occupations are not distinct parts of London’s economy, but are integrated into the production processes of other firms. One aspect of Correspondence Address: Neil Lee, Department of Economics, Lancaster University Management School and The Work Foundation, 21 Palmer Street, London, UK. Email: [email protected] # 2013 Taylor & Francis


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this is innovation, with the creative industries used to help create new products, services and processes. The scale of the creative industries in London and their links into wider production processes make them important subjects of research, with implications for the wider literature on creativity, innovation and cities. Yet, studies of creative industries in the capital are normally case studies of individual sectors or neighbourhoods (Pratt, 2009). Little research has considered the city scale, and none has focused on innovation. This raises important questions: are London’s creative industries particularly innovative? And what role do creative occupations play in innovation in London? Moreover, despite wide literatures on both the creative industries and innovation, the link between the two has been “relatively neglected” (Sunley et al., 2008, p. 676). While there has been discussion on the creative “industries” and innovation (e.g. Bakshi & McVittie, 2009; Mu¨ller et al., 2009), relatively less research has considered the impact of creative “occupations”. Yet, creativity is not limited to the creative industries (Vinodrai, 2006; Cunningham, 2011), and studies have found that creative occupations are often a good predictor of regional growth (Boschma & Fritsch, 2009). This article uses the 2007 London Annual Business Survey (LABS) to address this evidence gap. It asks two principal questions: (1) Are creative industries firms more innovative than other firms in London? (2) Are firms in sectors with high proportions of creative occupations in their workforce more innovative than other firms in London? These issues are of general importance to research on this topic, but they are of particular importance to research on London’s economy. The city is seen as having a successful, innovation-led economy. Yet, traditional measures of innovation, such as patents, fail to portray it as such, a situation Wood (2009) has described as the London innovation “paradox”. The capital reflects the idea of “hidden innovation” where innovation is not captured in official statistics (Simmie & Sennett, 2001; Miles & Green, 2008). The creative industries may be an important part of the effect. We test the relationship between the creative industries, a measure of creative occupations and four measures of product and process innovation. Despite prior expectations, we find no evidence that the creative industries are more innovative by any measure. However, firms in sectors with more creative occupations in their workforce are significantly more likely to introduce new product innovations, a finding robust to controls for firm characteristics, sector and whether the firm engages in other innovative activity such as R&D or collaborative ventures. This suggests that the integration of creative occupations into firms in the capital may be an overlooked driver of product innovation. The results suggest studies of innovation may need to consider occupations as an innovative input. The article builds on an emerging literature in economic geography considering innovation processes in the creative industries and how they relate to place (Sunley et al., 2008; Davis et al., 2009; Gwee, 2009; Cooke & De Propris, 2011). In doing so, it also contributes to the literature on innovation in the creative industries (Schweizer, 2003; Tschang, 2007; Mu¨ller et al., 2009). The article begins to address Miles and Green’s (2008) suggestion that innovation surveys should consider the creative industries, and highlights the potentially important contributions of (and problems with) this approach. The main methodological novelty is the introduction of a measure for “creative

Creative Industries, Occupations and Innovation

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occupations” to test whether creative employment is used as an intermediate input in innovation processes (Cunningham & Higgs, 2009; Cunningham, 2011). It is the first study to test these effects for London, a highly important city for the creative industries. The article is structured as follows. The next section outlines the benefits of large cities for the creative industries, and considers the creative industries in London. The third section discusses the literature on the creative industries and why they might be more innovative. The fourth section outlines the data used and describes a model of innovation processes in firms. The fifth section outlines the results of a series of logistic regression models investigating the determinants of innovation in firms in London. The final section concludes with the implications for policy and further research.


The Creative Industries and Innovation in London Cities, Innovation and the Creative Industries Cities in general, and London in particular, have important benefits for both the production of cultural goods and innovation more generally. Creative firms benefit from a wide group of, often more affluent, potential consumers (Hall, 2000). The classic Marshallian agglomeration economies of specialized customers and suppliers, wide and deep labour markets and knowledge exchange are all important for creative firms (Marlet & van Woerkens, 2007; Comunian, 2011). The first Marshallian advantage is the ease of both buying from and selling to other creative firms. Theoretical perspectives have suggested that creative industries firms may use collaboration with other specialized suppliers and firms (Stam et al., 2008; Mossig, 2011). Locating close to potential collaborators is important for reputation, productivity and availability of specialized businesses that may buy creative services (Pratt, 2006). Secondly, cities also provide access to specialized labour markets. This may be particularly important for creative firms, where production is often organized on a project-byproject basis which requires the assembly and re-composition of project teams (De Propris et al., 2009). The creative industries may also require highly specialized, skilled individuals to work in them (Vinodrai, 2006). In part because of this, there may be a high proportion of freelance employment and processes of sub-contracting between creative firms and the self-employed (De Propris et al., 2009; Comunian et al., 2010). Finally, the density of cities makes them sites of the exchange of knowledge, or “buzz” (Storper & Venables, 2004). Proximity allows face-to-face communication, the visual exchange of knowledge and facilitates the transmission of tacit knowledge between individuals. For creative firms, which may be reliant on the state of the art and so require knowledge of rapidly changing fashions, this may be particularly important (Power, 2002). Alongside this, cities may offer more prosaic benefits: access to institutions such as art galleries, music venues and theatres. There are reputational benefits to location in particular cities or neighbourhoods within them. For example, the need to create an established reputation, trust and ease of access means that advertising firms are commonly located in particular parts of London (Pratt, 2006). Because of this, international evidence suggests that the cultural industries tend to be located in major urban areas (Power, 2002; Marlet & van Woerkens, 2007; Stam et al., 2008; Mossig, 2011). Research has increasingly considered the role that different cities play in national innovation systems (Therrien, 2005). Larger cities have traditionally been viewed as

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performing more specialized functions and selling more specialized goods. This view has traditionally focused on “sectors”, but recent work has found that cities in the United States are increasingly focused on performing particular “functions” in the spatial economy (Duranton & Puga, 2005). In a seminal paper, Duranton and Puga (2001) suggest that firms innovate in large “nursery” cities before moving routine production processes to smaller, less expensive places. London may well be one of these “nursery” cities with the density and diversity of economic mass and both national and international links proving an ideal place to create new ideas (Lee & Nathan, 2010; Fitjar & Rodrı´guez-Pose, 2011; Nathan & Lee, 2011).


London’s Creative Industries London has historically been an important location for the creative industries. This built on historical strengths in publishing, but also the capital’s strengths in the entertainment industries. Writing of publishing in the 1800s, Jerry White argued that As a centre of intellectual production, London’s position in the English speaking world was scarcely less pivotal than its role as world finance capital. And in England itself no greater industry was concentrated more in London than the writing, making and distribution of the printed word. (White, 2008, p. 226) These historical strengths are represented in the city’s position now, with the creative industries overrepresented in London’s economy. As a hub for trade and migration, the city is open to new ideas and has attracted industries reliant on information. Affluent individuals in the capital provide consumers for cultural goods. Moreover, as an affluent, diverse city London has many of the characteristics that might be required of creative cities (Hall, 2000). It is the location of many of the nations artistic and cultural institutions, ranging from international art galleries such as the Tate Modern, centres for performance such as the South Bank Centre, and institutions such as the Royal Academy or Central St Martins School of Art and Design. While the creative industries are widely seen as important to London’s economy, attempts to demarcate the sector have proven controversial (Drake, 2003; Hesmondalgh & Pratt, 2005). An official definition is produced by the UK DCMS, which launched in 1998 a series of “Creative industries mapping documents”. These aimed to highlight the economic contribution of the sector and provide a rationale for public support, and were a move away from the more socially exclusive term “cultural industries” (Pratt, 2008; De Propris et al., 2009). The DCMS definition gives eleven creative sectors (although this has changed over time): Advertising; Architecture; Arts and Antique Markets; Crafts; Design; Designer Fashion; Film, Video and Photography; Software, Computer Games and Electronic Publishing; Music and the Visual and Performing Arts; Publishing, and Television and Radio. There are a number of problems with the DCMS definition. Sectors do not always match Standard Industrial Classifications, meaning that two subsectors, Design and Crafts, are not included in many empirical estimates of the sector’s size. The definition includes some “technical industries”, such as software, alongside industries that would traditionally be seen as part of the creative sector, like the arts. There is considerable diversity between the sectors contained within the definition (Hesmondalgh & Pratt, 2005; Freeman, 2010).



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And it ignores the complexity of the relationship between creativity and other industrial sectors (De Propris et al., 2009). Yet, despite these flaws, the DCMS definition has the virtue of consistence with other classifications, and has slowly become accepted as a definition, among policymakers at least, meaning empirical research based on it reflects the sectoral boundaries over which policy is often made. Freeman (2010) presents estimates of the number of jobs in London’s creative industries and creative occupations outside the sector. He estimates there are 386,000 jobs in the creative industries in London. De Propris et al. (2009) present location quotients for the creative industries in London in 2007 relative to the rest of the country, with relative specialization particularly strong in Radio and TV; Video, film and photography; Music and the visual and performing arts; Publishing; Advertising; Designer fashion and Software, computer games and electronic publishing. However, industry focused measures of innovation cannot capture the full influence of creativity in London’s economy, and Freeman (2010) also estimates there are 411,000 people working in creative occupations outside the creative industries. Table 1 gives information on the sort of occupations in this category. Recent estimates suggest the creative industries in London have been increasing rapidly, but creative occupations have grown even more rapidly. Between 1995 and 2007, total creative industries jobs (i.e. employment in creative industries in the capital) increased by around 40%, from 275,000 to 386,000 (Freeman, 2010). Over the same period, creative occupations performed outside the creative industries grew by over 70%: from 240,000 to 411,000 jobs. Freeman (2010) gives breakdowns for the proportion of creative occupations in each industry (these are based on the UK Labour Force Survey for 2008 and are not directly comparable with the figures given above). Within the creative industries, an average of 54% of people work in creative occupations. This is far higher than other sectors of the economy, where the average is 10%. There is some variation between sectors, however: 17% of workers in Manufacturing are in creative occupations compared with only 2% in Public Administration, Education and Health.2

Innovation and the Creative Industries Defining Innovation Innovation is a difficult concept to define. It is commonly understood as the commercial exploitation of new ideas (Fagerberg, 2005). Two types of innovation are commonly cited: product innovation, or the creation of new products and services, and process innovation, or new methods and processes of production. Early perspectives on innovation focused on simple linear models of input and output, with a set amount of research spending leading to an innovation produced within a single firm. This has been replaced by a view of innovation as a non-linear, complex and context-dependent process. Contacts between economic actors, the exchange of information and collaboration are seen as driving innovation, particularly in cities (Freel, 2000; Simmie & Sennett, 2001; Freel & Harrison, 2006). There is now widespread recognition that “few firms can innovate in isolation” (Freel & Harrison, 2006, p. 290). Research has also considered innovation processes in the creative industries, in which novelty, and so innovation, is seen as particularly important (Sunley et al., 2008). Because of a residual understanding of innovation as science based, many innovation

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N. Lee & E. Drever Table 1. Creative occupations in London, 2007/2008

Category Advertising Architecture


Crafts

Design Designer fashion Video, film and photography Music and the visual and performing arts Publishing

Software and electronic publishing Radio and TV

Occupations included in the category Advertising and public relations managers; Public relations officers; Marketing associate professionals Architects; Town Planners; Architectural technologists and Town Planning Technicians Glass and Ceramics makers, decorators and finishers; Furniture makers, other craft woodworkers; Pattern makers (moulds); Musical Instrument makers and tuners; Goldsmiths, Silversmiths, Precious Stone workers; Floral arrangers, Florists; Hand Craft occupations not elsewhere classified; Glass and Ceramics process operatives; Labourers in Building and Woodworking trades Design and development engineers; Artists; Graphic designers; Product, clothing and related designers. Product, clothing and related designers; Weavers and knitters Photographers and audio-visual equipment operators Authors, Writers; Actors, entertainers; Danvers and choreographers; Musicians; Arts officers, producers and directors Journalists, newspaper and periodical editors; Originators, compositors and print preparers; Printers; Bookbinders and print finisher; Screen printers Information and communications technology managers; IT strategy and planning professional Broadcasting associate professionals; TV, Video and Audio engineers

SOC 2000 Codes 1134; 3433; 3543 2431; 2432; 3121 5491; 5492; 5493; 5494; 5495; 5496; 5499; 8112; 9121

2126; 3411; 3421; 3422 5411 3434 3412; 3413; 3414; 3415; 3416 3431; 5421; 5422; 5423; 5424 1136; 2131 3432; 5422

Note: No occupations match the Art & Antiques sector or the Digital and Entertainment media. Source: Department for Culture, Media and Sport (2010).

studies still use R&D as an input and patents as an output (Acs et al., 2002; Crescenzi et al., 2007). Yet, such measures are clearly unsuitable for the measurement of innovation in the creative industries, where new products are unlikely to be patented and may not involve R&D spending (Miles & Green, 2008). Given this, and London’s specialization in the creative industries, it is unsurprising that innovation survey data show London’s innovation performance to be considerably better than R&D or patenting measures suggest (Wood, 2009). The Community Innovation Survey shows London had almost 5% of turnover derived from new or significantly improved products, the highest proportion of any UK region (Department for Trade and Industry, 2006).


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Innovation Processes in the Creative Industries The creative industries are seen as innovating in particular ways. Firstly, the literature on the creative industries has tended to suggest that they operate in a flexible environment, with groups of small firms engaged in networked production. Using a case study approach, Miles and Green (2008) outline a range of different sub-contracting arrangements. While these vary by sector, the dominant picture is a network of small creative firms linked through project-based organizational changes and movements. Swedish data suggest that creative industries firms are smaller than average, possibly indicating a fast moving business environment in which new firms are continually reformed (Power, 2002). Barriers to entry in some markets are low, so small firms can compete without needing economies of scale or large marketing budgets (Pratt, 2006). A second, related feature is the organizational complexity of creative firms (Vinodrai, 2006; Reimer et al., 2008). The fast-paced market structure in the creative industries relies on uncertain contacts, specialized skills and collaboration. As firms seek to make use of external knowledge in their production processes, this places a premium on collaboration as a source of innovation. Project work may dominate in these industries, as firms take on specific commissions and assemble short-term teams to carry them out. Through this, firms exchange information when creative individuals move from firm to firm, as “highly skilled workers act as mobile agents of innovation, bringing knowledge, ideas and practices into the firm” (Vinodrai, 2006, p. 239). Because of this, firms in the creative industries may be more likely to introduce new ways of working. Moreover, as innovation is driven by individuals doing creative work, creative occupations may also be important. Third, creative industries firms are assumed to be more reliant on innovation than firms in other sectors (Mu¨ller et al., 2009; Power, 2010). Firms need to differentiate products but often by building on the state of the art, meaning access to up-to-date knowledge is important (Asheim et al., 2007; Power, 2010). Firms will locate in cities like London to learn from each other (Therrien, 2005). “Combinative creativity” with the use and re-use of existing ideas can be used to produce incremental innovations of complex, symbolic products (Tschang, 2007). Creative industries firms might be more likely to create new products because of this, or to modify existing products to reflect new trends. Finally, an important aspect of the creative industries is their role in the innovation processes of other sectors (Bakshi & McVittie, 2009; Davis et al., 2009; Mu¨ller et al., 2009; Cooke & De Propris, 2011). This can happen in a number of ways. It may be because of the integration of creative products through one industry to another, as creative firms are integrated into the production processes of non-creative firms. This may lead to innovation as they use the creative industries as a source of ideas, or as an indicator that the firm is interested in improving and producing new products (Sunley et al., 2008; Mu¨ller et al., 2009). An important but neglected aspect of this may be non-creative firms employing people in creative occupations such as marketing, design or product development (Vinodrai, 2006; Bakshi et al., 2008). This might occur through the impact of a designer in a manufacturing firm, for example (Bryson et al., 2008; Reimer et al., 2008; Sunley et al., 2008). It might indicate a firm which is more willing and likely to engage in innovation, or it may be that the introduction of an creative job in a firm leads to innovation after this decision. However, only a small number of empirical studies have considered linkages between the creative industries and innovation in other sectors. Bakshi et al. (2008) test the relationship between creative employment and innovation using data for 2002 from the


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Community Innovation Survey. They find no statistically significant link with product innovations overall, but a weakly positive relationship with novel product innovations (significant at the 10% level). Bakshi and McVittie (2009) test two mechanisms through which creative industries influence innovation in the wider economy: knowledge acquisition between suppliers and customers, and; cooperation between suppliers and customers. They use input – output tables to establish relationships between the creative industries and other sectors, and then run logistic regressions for firm level innovation outcomes. They find firms which purchase more creative products also introduce more product innovations, but that there are less clear relations with other types of innovation. Using a survey of Austrian firms, Mu¨ller et al. (2009) show that the creative industries contribute new ideas to other firms, amend other products or help in the marketing of process innovations. They show that the creative industries tend to be more innovative than other sectors, although there is considerable diversity between different parts of the creative industries. While the relationship between the creative industries and product innovation is clear, the results for process innovation are less clearly defined. However, a wider literature does consider the role of certain occupations in economic growth. Research on the “creative class” has emphasized the importance of a set of creative occupations to innovation: a “creative core” of scientists and engineers, traditionally creative employment such as actors, poets and novelists, and “creative professionals” which includes those in healthcare and the law (Florida, 2002; Nathan, 2007). Thus, there is some overlap between the “creative core” and the measures used here. While there is some controversy around Florida’s work, the evidence does suggest a link between particular occupations and urban success. Florida et al. (2008) show a link between artistic and entertainment occupations on regional development, independent of any effect from human capital. Research on the UK shows London performing strongly on all measures of the creative class (Huggins & Clifton, 2011). Other work on the creative industries highlights the extent of creative occupations being performed across the entire economy, rather than just in the creative industries. The “creative trident” approach is one way of analysing this (Higgs et al., 2008; Cunningham & Higgs, 2009; Cunningham, 2011). The approach divides creative work into three groups: (1) specialist mode—those in creative occupations in creative industries; (2) support mode—workers doing non-creative occupations in the creative industries; and (3) embedded mode—workers doing creative occupations in non-creative sectors of the economy. Research on the creative trident has suggested that embedded creative workers can be seen as intermediate inputs in innovation processes in other sectors (Cunningham & Higgs, 2009). This is one of the core relationships this article seeks to test.

Data and model Data The main source of data is the 2007 LABS. This is a large-scale survey conducted by the London Development Agency, the body responsible for economic development in the capital at the time. It consists of over 4000 business units across the capital sampled within the calendar year. Excluding businesses where there are missing values for the variables used here, the final sample is just under 3000 firms. The sample is not representative of industrial structure, but it is stratified geographically meaning that it is representative of


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London’s five sub-regions. Variables for occupational structure and qualifications in each sector are taken from the Annual Population Survey (APS). The Model The basic model used here is a firm-level innovation production function, similar to other studies (e.g. Fitjar & Rodrı´guez-Pose, 2011). The model is estimated as a probit where the outcome is that innovation takes place:


INNOVi = a + b1 CIi + b2 COCCi + b3 FIRMi + b4 ACTIVITYi + w + 1 For firm “i”. Where INNOV is a measure of whether the firm engages in one of four types of innovation, CI is a variable for whether the firm is in the creative industries, COCC is a variable for the proportion of employees in the sector in London who work in creative occupations at the two digit SIC classification, FIRM is a vector of variables to account for the basic characteristics of the firm, these being size, age, whether the firm is an HQ, whether it has international bases, management skills and whether it is a Public Limited Company (PLC), ACTIVITY is a set of variables that control for the innovation-related activities of the firm. These are whether the firm collaborates, undertakes R&D and buys inputs from abroad. “w” is one of 13 sector dummies (with the creative industries being the 13th) and “1” is the error term. Table 2 gives details of the dependent variables and their sources. Measuring Innovation Few studies have used innovation surveys to investigate innovation in the creative industries, in part because of difficulties in the measurement of innovation (Mu¨ller et al., 2009). To address this problem, four different measures of innovation are used here. Each of these is a binary variable that is 1 if a firm innovates in this way and 0 otherwise. The first two variables are for product innovation. These are whether the firm has introduced (1) a new or significantly enhanced product or service or (2) a major modification to existing products or services in the previous 12 months. As firms in the creative industries are expected to produce more new products, and much of the production in the industries revolves around minor changes to existing products, both of these would be expected to be positive with the creative industries. These are the best available measures of product innovation, although they may not account for whether the products are new to the firm or simply imitations of new products elsewhere.3 The next two variables are for process innovation. These are (3) whether the firm has introduced new equipment and (4) whether the firm has introduced new working practices in the past 12 months. The interpretation of the latter is clearer, and given common portrayals of creative industries as flexible groups of team-based production systems, the creative industries would be expected to be more innovative by this measure. It is less clear that creative industries firms are more likely to introduce new equipment. As they may have lower barriers to entry than other sectors, they might actually be less likely to innovate in this way. While questions such as these are widespread in the innovation literature, all measures of innovation have limitations. Self-reported data may be subjective to the interpretation of the interviewees. Different sectors may introduce different products at different rates.

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N. Lee & E. Drever Table 2. Variable list

Domain Innovation

Variable New product Modified product New equipment


Firm characteristics

New working practice Creative industries Creative occupations Size (ln) Age (ln) PLC International HQ Management skills NVQ4 Sector Dummies

Innovative activity

Collaborative activity R&D Buys abroad

Description Whether the firm has introduced a new or significantly enhanced product of service in the previous 12 months Whether the firm has introduced a major modification to existing products or services in the previous 12 months Whether the firm has introduced new equipment in the previous 12 months Whether the firm has introduced new working practices in the previous 12 months Whether the firm is in the creative industries or not Creative occupations as percentage of employment in two digit sector (from Annual Population Survey) Total employment in the firm (ln) Total age of the firm (ln) Whether the firm is a publicly limited company or not Whether the firm is under international ownership Whether the unit in question is the HQ or not Management skills of the workforce (calculated using Principal Components Analysis) Percentage of employees in two digit sector qualified to NVQ4 and above (from Annual Population Survey) One of 12 ONS sector variables: These are: Primary and Utilities; Printing and Publishing; Other Manufacturing; Construction; Wholesale and Retail; Hotels and Restaurants; Transport and Communications; Banking and Finance; Business and Professional Services; Education, Health and Social Work; Other Community Services Whether the firm engages in collaborative activity (1 if firm collaborates) Whether the firm invests in R&D or not (1 if firm invests in R&D) Dummy variable for importing (1 if firm imports)

All variables from the LABS unless otherwise stated.

For example, retail firms may introduce new products more rapidly than pharmaceuticals, but these products may be less “innovative” in some senses. Much of this effect will be controlled for using sectoral dummies, but some of any variation will be due to these effects—this is unavoidable. The advantage of these approaches is that they are valid when studies wish to compare innovation processes in the creative industries with those in other sectors (Mu¨ller et al., 2009). However, they may not be able to fully capture the nuances of different innovation processes across sectors, a particular problem with the creative industries (Stoneman, 2009). This is an ongoing problem with research in this area, which will require highly specialized innovation surveys to address. In this case, controlling for a wide number of potential innovation processes, applying sectoral dummies and considering the analysis with caution is the best way of dealing with definitional issues around innovation.


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Table 3. Percentage of firms innovating by creative industries status Product innovation

Other industries Creative industries Total

Process innovation

Observations

New product innovation

Modification of existing product

New equipment

New working practices

2619

29.85

25.89

23.02

25.35

355

29.86

26.20

19.72

22.82

2974

29.86

25.92

22.63

25.05


Source: London Annual Business Survey.

The limitations of these measures may be more acute in the creative industries, as industries using symbolic production tend to involve learning by doing and face-toface interaction rather than formal R&D processes (Chapain et al., 2010; Martin & Moodysson, 2011). Such symbolic innovations will have complex relationships with new technological innovations, particularly where new technology allows the production of new, creative products (Schweizer, 2003). Stoneman (2009) describes this as “soft innovation” as both aesthetic innovation or the production of new creative content. These innovations vary in their significance, but they are most likely in the creative industries. Table 3 gives the proportion of creative industries firms that innovate according to each of these measures. From a sample of 2974 firms, 355 are in the creative industries, just under 12%. As noted, there is no overall “creative industries” effect on any of the innovation measures. Creative industries firms are equally likely as normal firms to introduce new and modified product innovations, with around 30% and 26% of both sets of firms innovating in this way. Creative industries firms are slightly less likely to introduce new equipment: 20% of creative industries firms do this compared with 23% of other firms. They are also less likely to introduce new working practices, with 23% of creative industries firms innovating in this manner relative to 25% of other firms. In summary, there is little difference in the extent to which creative industries firm introduce product innovations, but they are slightly less likely to introduce process innovations.

Independent Variables The measure of the creative industries is augmented with an occupational measure: the share of creative occupations in each two-digit SIC code in London.4 The link between innovation and creative occupations has been neglected, in part because most innovation surveys fail to include a question for whether individual firms include staff in these occupations. As the LABS does not include such data, a sector-based measure is calculated from the APS. The APS gives a sample of 14,164 individuals who are employed in London in the period from January to December 2007. Of these, according to the DCMS definition 10.49% work in creative occupations. This is collapsed by a two-digit sector to create a sectoral variable: the percentage of employees in each two-digit sector who work in creative occupations.


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In addition, we include two further sets of firm-related controls. The first set refers to the basic characteristics of the firm. Larger firms are more likely to introduce new products and services so to control for this we use the log of total employment. Similarly, older firms are often less likely to innovate as they have products already under production. This is controlled for by the log of firm age. A variable for whether a firm is a PLC is included as legally formed firms may respond to shareholder pressure to introduce new products. We control for whether the unit in question is the firms headquarters and whether the firm operates in more than one country. Thirteen sectoral dummies are also used, one of which is for creative industries firms.5 The LABS does not ask for information on the qualifications of the management. We control instead for management skills, using a single variable created using Principal Components Analysis (PCA).6 The variables are whether the firm has a business plan, staff training plan, management accounts, sales and marketing plan, equal opportunities, a system to monitor recruitment and selection and a business emergency plan. Together these should create an indicator of how well managed a firm is. Better-managed firms should be more innovative. The second set of variables relate to the innovative-related activities. These are included to check that any innovation-related effect is not due to the propensity of creative industries firms to invest more in activities designed to lead to new products or processes. Research on the nature of innovation suggests that firms who collaborate with external organizations are more innovative (Freel, 2000). A dummy variable for whether a firm performs any collaborative activity of not, is used. There is also considerable discussion on the importance of R&D for firms, with the assumption that firms that invest in R&D do so with the aim of innovating. A dummy variable for whether a firm invests in R&D is used for this. Note that two important limitations to this are that we cannot tell the value of R&D expenditure, and nor do we know whether the R&D took place internally or externally to the firm.

Results: Innovation in London Product Innovation Table 4 gives the results for product innovation. Each of the models includes 13 sector dummies, one of which is for the creative industries. For conciseness, we only report the result for the creative industries sector dummy. The first two columns test the creative industries and creative occupations variables individually. These show no significant relationship between the creative industries and the introduction of entirely new products. Rather than the expected positive relationship, the result is in fact negative and not significant. However, the creative occupations variable performs more strongly: when only sectoral dummies are used, firms in sectors with high proportions of people employed in creative occupations are significantly more likely to introduce new products. This is a raw test of the results, and may be explained by the other characteristics and activity of these firms. In column three controls are introduced for the characteristics of the firm. The main results change little: controlling for size, age, whether the unit is an HQ or not, international links, legal status, the qualifications of the workforce and the skills of the

Table 4. Creative industries, creative occupations and product innovation in London

Dependent variable

(2)

(3)

(4)

Product innovation: New product innovation

Sector dummies Constant

Yes Yes 20.330∗∗∗ 20.768∗∗∗ (0.119) (0.0953)

Yes 20.684∗∗ (0.313)

20.258∗ (0.156) 0.937∗∗∗ (0.322) 0.0102 (0.0244) 20.0481∗∗ (0.0237) 0.173∗∗ (0.0838) 0.196∗∗ (0.0822) 0.362∗∗∗ (0.101) 0.570 (0.382) 0.0867∗∗∗ (0.0170) 0.344∗∗∗ (0.0609) 0.412∗∗∗ (0.0615) 0.00516∗∗∗ (0.00109) Yes 21.097∗∗∗ (0.321)

Observations Pseudo R2

2974 0.0169

2974 0.0727

2974 0.116

Creative industry firm

20.198 (0.138)

Creative occupations by sector (%) Size (ln)

1.053∗∗∗ (0.273)

Age (ln) HQ International PLC NVQ4 by sector (%) Management skills

20.149 (0.153) 0.924∗∗∗ (0.316) 0.0382 (0.0235) 20.0645∗∗∗ (0.0233) 0.219∗∗∗ (0.0812) 0.265∗∗∗ (0.0793) 0.321∗∗∗ (0.0992) 0.255 (0.375) 0.121∗∗∗ (0.0163)

Firm collaborates R&D activity Buys from abroad

2974 0.0212

(6)

(7)

(8)

Product innovation: Modification of existing product 0.0646 (0.146)

Yes 20.702∗∗∗ (0.127)

Yes 20.878∗∗∗ (0.0974)

Yes 20.835∗∗∗ (0.323)

0.0141 (0.163) 0.730∗∗ (0.328) 0.00437 (0.0244) 0.00474 (0.0248) 20.0393 (0.0877) 0.179∗∗ (0.0823) 0.0770 (0.103) 20.0159 (0.388) 0.114∗∗∗ (0.0174) 0.325∗∗∗ (0.0619) 0.483∗∗∗ (0.0622) 0.00194∗ (0.00113) Yes 21.180∗∗∗ (0.326)

2974 0.00885

2974 0.0132

2974 0.0627

2974 0.108

1.057∗∗∗ (0.275)

0.125 (0.161) 0.777∗∗ (0.322) 0.0360 (0.0238) 20.0127 (0.0242) 0.0270 (0.0850) 0.214∗∗∗ (0.0794) 0.0550 (0.0996) 20.230 (0.388) 0.151∗∗∗ (0.0169)

1989

Robust standard errors in parentheses. P , 0.1. ∗∗ P , 0.05. ∗∗∗ P , 0.01. ∗

(5)



(1)


1990

N. Lee & E. Drever

management, creative industries firms in London are no more innovative than those in other sectors. However, firms in sectors employing people in creative occupations are more likely to introduce new products. Finally, in column four we introduce three further variables to control for whether firms engage in innovation-related activity. Yet, even these controls make no difference to the main results: creative industries firms are no more likely to introduce innovations than firms in other sectors, with firms in sectors which employ individuals in creative occupations more likely to. Indeed, there is even a weakly significant negative result showing that firms in the creative industries are—controlling for firm characteristics, sector and whether they engage in innovation-related activities—actually less likely to introduce new products than other firms. The control variables provide some insight into the drivers of innovation in London’s firms. Larger firms are more likely to introduce product innovations, while older firms are less so. When the firm sampled is an HQ, has international links or is a PLC it is also more innovative in this way. Firms with better managerial skills are more innovative, although sectoral skill levels are not significant. It might simply be that human capital is less important than the activity performed by firms, and this finding supports other work suggesting the effect of occupations performed is distinct from that resulting from the level of human capital (Florida et al., 2008). Innovation-related activity also, as expected, matters. Firms that collaborate, perform R&D activity and introduce new products from aboard are more likely to introduce product innovations. In short, there is no evidence that the creative industries are more likely to introduce new product innovations than other sectors, in London at least. Controlling for their activities, they may actually be less likely to. This provides a contrast with the literature on the creative industries, which tends to assume that these firms are more innovative (Mu¨ller et al., 2009). One reason for this result may be that the measure of innovation is too blunt, and is unable to capture the value of innovations in one sector compared with another. It might also be that some creative industries firms such as advertising agencies, may be used create innovation in other sectors. Yet, it is a useful reminder that innovation is not limited to particular parts of the economy. Other research focused on London has suggested that the high levels of innovation among other firms means that the creative industries—while innovative—are not disproportionately so (Chapain et al., 2010). Creative occupations, in contrast, appear a robust driver of product innovation. Firms in sectors that employ more staff in creative occupations are more likely to introduce new products and introduce modifications to existing products. This finding reflects the literature on creative occupations, which suggests that firms introduce creative individuals to create innovation (Vinodrai, 2006). The effect is more conclusive than previous work (Bakshi et al., 2008). The implication is that innovation in non-creative industries may be driven by individuals in creative occupations. In London, the sectors where this happens are those where firms are more innovative. The second implication of this finding is about the role played by London in the economy. Different cities perform different functions in the economy, with larger cities tending to specialize in cognitive and creative functions (Duranton & Puga, 2001; Lorenzen & Vaarst Andersen, 2009). These results show that the creative function played by London may go beyond that played by the industrial base of London, with the functions played by firms in other industries a more important driver of innovation. London’s creative industries tend to specialize in core creative values, and this finding may reflect that (De Propris et al., 2009). Given that this article is focused on London alone it is not


1991

possible consider this hypothesis further, yet future resarch may want to test it using a cross-section of cities.


Process Innovation In Table 5 we consider the impact of the creative industries on two measures of process innovation: new equipment and new working practices. Columns one and two consider the raw results for the creative industries and occupations measures, controlling only for sector. Creative industries firms are actually less likely to introduce new equipment than firms in other sectors, although there is no effect for creative occupations. When controls are introduced (columns three and four) the result for creative industries loses significance, implying that much of the effect is the characteristics of the firms such as age, size or ownership structure. Moreover, as the coefficient reduces further once controls for innovation-related activity are introduced the other activities of the firms may be driving the initial result. The results also give insights into the introduction of new equipment in firms. Older firms, those which are PLCs, which are from more skilled sectors and which have better management skills are more likely to introduce new equipment. Larger firms are more innovative in this way, although this is driven by their greater likelihood of engaging in innovation-related activity. Firms that perform R&D are more likely to introduce new equipment. Those which buy from aboard are, surprisingly, less likely to introduce new equipment. One reason might be that these firms buy production from elsewhere so they have less need for equipment to create new goods or services. Taken with the results for simple cross-tabs (Table 3), these results suggest that creative industries firms are—if anything—actually less likely to introduce new equipment. This result fits with a view of the sector has having low barriers to entry and fewer fixed costs for new entrants (Power, 2002; Jayne, 2005). In a situation with rapidly changing consumer preferences and project-based work, firms in the creative industries will tend to invest less in major new equipment to compete. Instead, competitive advantage can be gained from access to new knowledge, collaborative activity and specialized human capital. For creative occupations, there is no clear theoretical reason either way to expect firms to introduce new equipment and so this result is not surprising. Columns five to eight consider the final form of innovation: new working practices. In the basic regressions for new working practices (columns five and six) neither creativity variable is significant. Both are actually negative, suggesting little if any role for the creative industries or occupations in this measure of process innovation. In columns seven and eight basic controls and then innovation-related controls are introduced. The results for the creative industries and occupational measures change little. This does not appear to be a situation where rapidly changing organizational forms force new ways of working on creative industries firms. It may be that instead firms in the sector have already adapted to new ways of working. That firms in sectors employing individuals in creative occupations are no more or less innovative is less surprising, as there seems no clear rationale for them to do this more or less. And these results may disguise considerable variation within the sector (Grabher, 2002). Both the unit in question being an HQ and the sectoral skills measures are significant and positive, implying firms with these characteristics are more likely to introduce new working practices. When the measures for the innovation-related activity are introduced

(1)

(2)


Creative industry firm

20.332 (0.144)

0.249 (0.292)

Age (ln) HQ International PLC NVQ4 by sector (%) Management skills

20.228 (0.154) 0.238 (0.341) 0.0379 (0.0244) 0.0526∗∗ (0.0244) 0.0265 (0.0866) 0.132 (0.0835) 0.176∗ (0.101) 0.636 (0.391) 0.0635∗∗∗ (0.0174) 0.0892 (0.0636) 0.334∗∗∗ (0.0637) 20.00309∗∗ (0.00122)

0.0134 (0.149)

R&D activity Buys from abroad

(6)

(7)

(8)

Process innovation: New working practices

20.170 (0.152) 0.322 (0.340) 0.0541∗∗ (0.0242) 0.0444∗ (0.0243) 0.0629 (0.0855) 0.0997 (0.0811) 0.183∗ (0.0993) 0.592 (0.391) 0.0837∗∗∗ (0.0169)

Firm collaborate

Observations Pseudo R2

(5)

Process innovation: New equipment ∗∗

Creative occupations by sector (%) Size (ln)

20.000114 (0.00117) Sector dummies Constant

(4)

0.163 (0.283)

0.150 (0.163) 20.0697 (0.337) 0.0531∗∗ (0.0242) 20.0636∗∗∗ (0.0244) 20.0438 (0.0845) 20.0491 (0.0821) 0.180∗ (0.100) 0.0660 (0.392) 0.184∗∗∗ (0.0172)

0.0777 (0.164) 20.159 (0.337) 0.0295 (0.0246) 20.0532∗∗ (0.0247) 20.0897 (0.0859) 20.0648 (0.0845) 0.195∗ (0.103) 0.208 (0.396) 0.158∗∗∗ (0.0175) 0.188∗∗∗ (0.0626) 0.410∗∗∗ (0.0626)

YES 20.519∗∗∗ (0.122)

YES 20.908∗∗∗ (0.0993)

YES 21.261∗∗∗ (0.330)

YES 21.358∗∗∗ (0.331)

YES 20.758∗∗∗ (0.129)

YES 20.781∗∗∗ (0.0985)

YES 20.822∗∗ (0.331)

YES 21.040∗∗∗ (0.334)

2974 0.0109

2974 0.0112

2974 0.0377

2974 0.0532

2974 0.00294

2974 0.00304

2974 0.0677

2974 0.0930

Robust standard errors in parentheses. ∗ P , 0.1 ∗∗ P , 0.05. ∗∗∗ P , 0.01.

N. Lee & E. Drever

Dependent variable

(3)

1992

Table 5. Creative industries, creative occupations and process innovation in London


1993

in column six, younger firms are more likely to introduce new working practices. Firms with better management skills are also more likely to, as are those which collaborate and engage in R&D activity. Research on the creative industries suggests that project-based work may lead to teams being assembled for relatively short time periods before starting new, different projects (Grabher, 2002). This form of process innovation does not appear to be reflected in the results which contrast with a view of the creative industries as being sectors in which project teams are continually reinvented and so new working practices are regularly introduced.


Conclusion London’s advantages as an open, diverse and large capital city mean that it is seen as a hub of innovation in the creative industries (Hall, 2000). Yet, the results here suggest that London’s creative industries are no more innovative than other sectors. Controlling for innovation-related activity, they may actually be less likely to introduce new products. This is surprising given assumptions about their innovative nature. One explanation is that in London other sectors are equally innovative (Cooke & De Propris, 2011). It may also be because of the highly subtle nature of innovation in the capital. In a survey of creative industries and innovation across the UK, Chapain et al. (2010) show that while the creative industries are overrepresented in London, the creative industries in London are both less innovative than the rest of the economy—and less innovative than the creative industries in other regions. Yet, they suggest this may be because London’s creative industries specialize in “soft” innovation with highly nuanced, often aesthetic content which surveys do not capture. However, it appears that the integration of creative occupations across the economy is a significant driver of product, but not process, innovation (Vinodrai, 2006). This is the key result of this article, as few studies have investigated the integration of people doing creative jobs to innovation using firm-level data. It lends support to approaches such as the “creative trident” which suggest that creative occupations can be seen as an input into innovation processes (Higgs et al., 2008; Cunningham & Higgs, 2009; Cunningham, 2011). The effect is robust to the inclusion of controls for the main innovation-related activities firms might perform. One implication is the need to consider creative inputs in innovation studies, rather than focusing solely on science-based measures such as R&D. However, the measure for creative occupations used here is limited as it is a sectoral measure, and so ignores variations within sectors. Future surveys should consider a firmlevel measure of creative occupations. The research also improves academic understanding of innovation in London, which is driven less by creative industries firms in the capital and more by the integration of creative occupations into other firms. This accords with London’s innovation “paradox” as the city scored highly on measures of innovation, but not necessarily of the science-based aspects (Wood, 2009). Part of this effect may be driven by creative occupations. The role of cities is, it has been suggested, increasingly related to performing particular functions within economic systems, rather than creating particular goods (Duranton & Puga, 2005). This is particularly the case with cities high in the urban hierarchy, like London (Lorenzen & Vaarst Andersen, 2009). Its economy specializes in creative aspects of


1994

N. Lee & E. Drever

value production and this occurs both within industries and across industries. Future research using data for other cities may want to test this hypothesis. A wide number of studies have linked creative individuals, workers or the creative class with more economically successful cities and regions (Florida, 2002; Nathan, 2007; Boschma & Fritsch, 2009; Huggins & Clifton, 2011). Yet, macro-level studies are often unclear about the mechanisms through which creative workers lead to innovation in a city.7 This article outlines one way in which this might happen. Other studies suggest that there are independent effects from human capital and creative workers on regional productivity (Florida et al., 2008). It might be that the concentration of creative occupations in London attracts human capital to the city through its effect on quality of life in the city (Nathan & Lee, 2011), with this creating further innovative processes. While this article cannot test this relationship in full, it is an important relationship to be considered in future work. This article opens up a number of other avenues for future research. This article has used existing data to consider innovation in the creative industries, but future research should use specific research methods to capture innovation in the creative industries (see Mu¨ller et al., 2009). This article has also highlighted the potential importance of creative occupations in innovation, and a simple way of testing the results of this article would be to ask whether firms have employees in creative occupations. Alongside this, future research should consider creative sub-sectors. This article has considered the sector as a whole, as this is often the focus of policy, but this means hiding diverse experiences within the sector. Finally, this article has contributed to the literature with a study of firms in London, an important city for the creative industries. But London has a unique position in the urban hierarchy. Future research should consider whether the results hold in other cities.

Acknowledgements The authors thank Andre´s Rodrı´guez-Pose, Max Nathan, Simona Iammarino, Callum Lee, Ben Reid, Alexandra Albert, Dick Wiggins and two anonymous referees for comments and suggestions.

Notes 1. For this article we use the Department for Culture, Media and Sport (2010) definition of the creative industries for the 2003 SIC codes: Advertising (74.40); Architecture (74.20); Art and Antiques (52.48, 52.50); Designer Fashion (17.71; 17.72; 18.10; 18.21; 18.22; 18.23; 18.24; 18.30; 19.30;. 74.87); Video, Film and Photography (22.32, 74.81, 92.11, 92.12, 92.13); Music and the visual and performing arts (22.14, 22.31, 92.31, 92.32, 92.34, 92.72); Publishing (22.11, 22.12, 22.13, 22.15, 92.40); Software, computer games and electronic publishing (22.33, 72.21, 72.22); and, Radio and TV (92.20). However, as they are not fully captured by SIC codes, two of these sectors (Crafts and Design) cannot be included in the final model (Department for Culture, Media and Sport, 2010). 2. Freeman (2010) gives the following breakdown for “creative intensity” for a selection of sectors: Manufacturing (17%), Banking Finance and Insurance (11%), Construction (8%), Transport, Storage and Communications (4%), Distribution, Hotels and Restaurants (3%) and Public Administration, Education and Health (2%). For creative industries the average is 54%, broken down as: Architecture (42%), Fashion (42%), Leisure Software (45%), Publishing (50%), Advertising (58%), Radio and Television (59%), Film and Video (67%) and Music and Performance (68%).


1995

3. These are similar to the questions used in the Community Innovation Survey, with the main difference being that LABS investigates innovation over the previous year rather than the past three. 4. Two digit SIC codes, rather than a more detailed level, are used to construct the occupational measure because three or four digit SIC codes cannot always be matched with the LABS dataset. 5. Only limited sectoral controls are used for a number of reasons. Collinearity between particular variables and more detailed sectoral dummies is a problem, which leads to a reduction in observations which may not be random. The focus is on the creative industries as a whole, rather than individual creative sectors, and this dummy allows them to be considered as a whole. 6. The factor loadings are 0.3894, 0.4047, 0.3513, 0.3205, 0.4129, 0.4044 and 0.3527, respectively. 7. We are grateful to an anonymous referee for this point.


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