Entrepreneurship and creative industries in emergent and developed countries
Luciana Lazzeretti ()
Dipartimento di Scienze per l'Economia e l'Impresa, Università degli Studi di Firenze
Rafael Boix Domènech ()
Department d’EstructuraEconòmica, Universitat de València, Valencia, Spain.
Daniel Sánchez Serra ()
Innovation and Measuring Progress Division, OECD
Subject area: Special Creative industries and entrepreneurship
Abstract:Although there is partial evidence about the positive effects of creativity on entrepreneurship in developed countries, this relationship has hardly been studied for developing countries, and so far general discussion and evidence encompassing both types of countries have not been introduced. This article provides, for the first time, evidence about theinterdependences between specialization in creative industries and entrepreneurship in a sample of 81 developed and developing countries in Europe, Asia, North and South-America, Africa and Oceania.The analysis is possible due to the elaboration of a new database crossing registers from the Global Entrepreneurship Monitor (GEM), OECD, Eurostat, The World Bank, WIPO, Orbis, and specialized reports. The database allows to differentiate culture-basedand copyright-basedindicators of creative industries, formal business-based and individual-based definitions of entrepreneurship, and high and low-quality indicators of entrepreneurship. The evidence suggests a higher specialization in creative industries does not positivelyinfluence all types of entrepreneurship but only those related to high-quality entrepreneurship (associated with opportunity, expectations of fast growth, introduction of new products, with international orientation, or adopting a corporate form), whereas it is negatively correlated with low-quality types of entrepreneurship associated with need and the adoption informal forms.
Keywords: creative industries; entrepreneurship
JEL codes: Z10; L26
1
Creative industries and entrepreneurship:an application todeveloping and developed countries
1. Introduction
The relationship between creative industries and entrepreneurship iscentral to understanding the rise of creative industries towards the end of the 20th centuryand its growing importance in the 21st century within the context that Scott (2014) calls cognitive-cultural capitalism.
Most previous studies on creative industries and entrepreneurship focusexclusively on creative class constructs and measures applied to developed countries. Yet, the manner and extentof the overall economic influence of creative industries on entrepreneurship, and in particular in both developed and developing countries have not been investigated. Thus, a broader analysis of creative industries’influence in developed and developing countries is needed. This article attempts to empirically examine creative industries, entrepreneurship, and their interrelationships in 81 developed and developing countries.
The present analysis is possible due to the elaboration for this article of a new databaseincluding 81 countries in Europe, Asia, North and South-America, Africa, and Oceania from the Global Entrepreneurship Monitor, Eurostat, World Bank, World Intellectual Property Organization (WIPO), Orbis, and national reports. Usingthis new database, this study examined:i) whether the existing relationship between creative industries and entrepreneurship is a global phenomenonor specific to developed or developingcountries, ii) whether cultural and copyright approaches to creative industries have different effects on the variousnotionsof entrepreneurship according to the country’s stage of development, and iii) how different definitions of entrepreneurship are central to understanding the directionand intensity of the relationship that maylead to contradicting conclusions.
This paper is organized as follows:Section 2 introduces the literature on creative industries and entrepreneurship;Section 3 describes the datasets and indicators used to assess entrepreneurship and creative industries; Section 4 provides a detailed mapping of creative industries and entrepreneurship in 81 countries and explores the relationship between creative industries and entrepreneurship; andconclusions are presented in Section 5.
2. Place-based creative industries and entrepreneurship: A literature review
Scientific literature has tried to relate creativity and entrepreneurshipaccording to geographical location using a wide notion of creativity or those related to the creative class[1].From a theoretical perspective, a higher level of specialization – in terms of creative class or creative industries – is associated with higher rates of entrepreneurship. Six explanations have been suggested.
First, this relationship is attributed to theco-occurrence of both creativity and an entrepreneurial attitude among the workforce and organizations in places. Matthews (2007) and Fritsch and Sorgner (2014) remark that both creativity and entrepreneurship are not completely different phenomena as they share common characteristics – processes, products, situations, persuasion, and potential – and operate in the same workspaces. Entrepreneurs apply creative processes, and entrepreneurship benefits from the use of creative thinking (new ideas, products, and business models).Thus, creativity (generation and exploration) directs entrepreneurship (discovery and exploitation)and both canultimately affect the innovation space.
A related explanation is the higherdegreeof entrepreneurship amongcreative people termed‘creative entrepreneurship’ (European Union, 2012). Florida (2002, 2003), Krauss and Sternberg (2014), and Acs et al. (2011)argue that creatives are more likely to establish new firms than other people would.Higher entrepreneurship ratesamong creatives and creative industries could be attributed to education, lifestyle, and self-management (Eikhof and Haunschild, 2006), as well as characteristics of creative industries: human and physical capital or firm size, higher creation of new goods and services, including radical innovation (Khaire, 2015), or instability and precariousness in certain professions and industries.Thisargument is not universally shared, since there is evidence that creatives in cultural industries perceive entrepreneurship as a detractor from “pure” artistic creation. Further, public intervention in cultural activities could also reduce entrepreneurship rates. Crombie (2011) provides an exhaustive review about creative entrepreneurship and their determinants in European countries.
A third explanation is the environment effect. According to Florida (2002, 2003), the creative class tends to concentrate in areas and cities wherefacilities for entrepreneurship (venture capital, infrastructure, public policies, etc.) are also available.According to Fritsch and Sorgner (2014), the creative class is an attribute that affects the level of entrepreneurship of places;consequently, creativity influences entrepreneurship. Indeed, Lee et al. (2004) find that the presence of creative people, such as ‘bohemians’, creates an environment that attracts other types of highly qualified human capital, which accelerates information flows, resulting in higher rates of entrepreneurial activity. For Westlund et al. (2014), the effects of creativity on entrepreneurship are mediated by their effect on social capital. Creativity is anelement of social capital andaffects norms, values, and networks, as well as influences social aspects of places, such as culture, knowledge, communication, leisure, production, and consumption.Consistent with Florida (2002, 2003) and Westlund et al. (2014), Stuetzer (2014) finds that the regional share of employment in the creative class (creative environment) is positively associated with individual perceptions of entrepreneurial opportunity.In addition, the creation of new firms may be prompted by the location of non-local firms. Moreover,as Florida (2002, 2003) and Bontje et al. (2008)note, creative environments attract creative and non-creative firms.A more integrated and structured explanation of environmental factors can be found in Scott’s (2006, p.1) theory of the creative field, a site of ‘(a) entrepreneurial behavior and new firm formation, (b) technical and organizational change, and (c) the symbolic elaboration and re-elaboration of cultural products’.
A fourth explanation is that creative industries provide highly specialized services (consulting, business skills, product and service development, design, marketing, commercialization, etc.) that are used by the local economy (European Union, 2012). Creative servicesfacilitate advantages and opportunities for new firms, and reduce the risk and costs for entrepreneurs, improving their survival and success rates.Similarly, Henry and de Bruin (2011) state that aheterogeneous set of creative industries can facilitate entrepreneurship.
A fifth explanation is associated with the sector life cycle (European Union, 2012). A part of creative industries comprises emergent sectors while other traditional sectors have been undergoing rapid transformationbecause of radical changes through technical progress. As a consequence, creative industries have grown faster than other parts of the economy.
Thesixth explanation is based on the creativity theory of knowledge spillover in entrepreneurship (Audretsch and Belitsky, 2013; Belitsky and Audretsch, 2014; Belitsky and Desai, 2016). This theory explains that creative environments (e.g. organizations or cities rich in creative class or human capital) create new ideas which are directly commercialized by creators or are recognized and then commercialized by other entrepreneurs (see also Boix and Soler, 2015). Consequently, creativity is a source of knowledge spilloversin entrepreneurship, while entrepreneurship intermediates the indirect relationship between creativity and economic development (creative filter). Audretsch and Belitsky (2013) find empirical support for this theory using a sample of European cities.
Empirical evidence suggests a positive causal relationship between creativityand entrepreneurship in most cases (see Krauss and Sternberg, 2014; Olim et al. 2015),especially for the creative class and bohemians, who are most used to measure creativity (Stolarick et al., 2011; Audretsch and Belitsky, 2013; Belitsky and Audretsch, 2014; Belitsky and Desai, 2016; Westlund et al., 2014; Stuetzer, 2014). However, other research has either been inconclusive or has found no evidence of this causal relationship (e.g. Malanga, 2004; and Olim et al., 2015).
3. Measuring creative industries and entrepreneurship
3.1. Measuring entrepreneurship
Entrepreneurship can be defined using top-down and bottom-up approaches (Ahmad and Seymoud 2008, p.5). The top-down approach uses theoretical entrepreneurship definitions proposed by scholarsfrom Cantillon (1975) - who defined an entrepreneur as a risk-taker in trade - to Schumpeter (1965) - for whom entrepreneurs are defined as individuals who exploit market opportunity through technical and/or organizational innovation. For Schumpeter (1934) an entrepreneuri) introduces a new good or new quality of a good; ii) introduces a new method of production; iii) opens a new market; iv) exploits a new source of supply of raw materials; or v)establishes new organisationsin any industry.
The bottom-up approach focuses on measurable characteristics of entrepreneurship. Entrepreneurship refers to a set of abilities that are difficult to measure and compare across individuals, regions, or nations; indicators identified in the literature are proxies, subject to criticism.A large set of studies have used self-employment data as a proxy for entrepreneurship because this data is available for a large number of regions and countries. However, self-employment data cannot differentiate between mixedlabour-market factors such as entrepreneurial pull and unemployment push, resulting in biases. Another typical set of indicators has relied on business data such as number of establishments, density of firms, business ownership, or firm demography (e.g. the World Bank and OECD databases). Since 1999, the Global Entrepreneurship Monitor (GEM) has compiled survey- and interview-based data for several countries, where theunit of analysis is the individual rather than the enterprise, measuring entrepreneurship and individual characteristics of entrepreneurs, such as motivations and attitudes towards entrepreneurship, involvement in entrepreneurial activity, and aspirations for their business.
Currently, only two sources of data cover a sufficiently large number of countries for this study: the GEM and the World Bank Database. Theyuse different but complementary approaches to entrepreneurship.
The GEMobtains entrepreneurial behaviour and attitudes for individuals in 108 countries since 1999 and is elaborated from a survey onvarious aspects of entrepreneurship in different phases of venturing (GEM 2014). The survey was designed to assess interdependence between entrepreneurship and economic development. In the GEM, entrepreneurship is defined as,‘any attempt at new business or new venture creation, such as self-employment, a new business organization, or the expansion of an existing business, by an individual, a teamof individuals, or an established business’ (GEM 2014, p.15).
This broad definition and the survey’s implementationallows for the inclusion of individuals engaged in entrepreneurship in the form of business and other legal status (e.g. self-employment, entrepreneurial employee activity), from both the formal and informal sector, of which the latter is particularly important for developing countries where the informal sector is especially important.
The basic indicator used in the GEM is the ‘total early-stage entrepreneurial activity’ (TEA) rate, defined as the percentage of 18-to-64-year-old who are either nascent entrepreneurs or owner-managers of a new business.The GEM differentiates between reasonsfor becoming an entrepreneur, providing the ‘relative prevalence of necessity-driven entrepreneurial activity’ and ‘relative prevalence of improvement-driven opportunity entrepreneurial activity’ rates. It also provides indicators about ‘new product early-stage entrepreneurial activity’, and ‘international orientation early-stage entrepreneurial activity’ (See see GEM, 2014; and Kelley et al, 2016) (See also Annex 1 for a more detailed description of the indicators). These indicators allowus to differentiate between high- and low-quality entrepreneurship (see GEM, 2014; Kelley et al, 2016).
The second source of dataon entrepreneurship is the World Bank Doing Business (WBDB)2009–2014 database of 137 countries. Unlike the GEM, WBDB data are obtained fromofficial business administrative registers of the countries and only covers limited-liability firms. The WBDB only provides two indicators: the entry of new firms(number of newly registered limited-liability firms during the calendar year), and new density (number of newly registered limited liability firms per 1,000 working-age people from 15–64 years).
The use of one or the other database is not without controversy (see Acs et al, 2008; Klapper et al, 2010), especially regarding the best way to measure entrepreneurship. In our case, we used both databases complementarily. The GEM database covers a greater variety and characteristics of entrepreneurship. The WBDB focuses on the creation of businessesin corporate form, capturing mainly high-quality entrepreneurship.
3.2. Measuring creative industries: Basic indicators
The database of creative industries shows the share of creative industries in national records of employment. This indicator is usually elaborated as follows (see Lazzeretti et al, 2008; Boix et al., 2012): first, a definition of creative industries is reached where certain sectors or activities are identified as creative. It is then applied to employment databases (or GDP, number of firms, etc.), to obtain the relative share of creative industries in a country, which is simple specialization in creative industries.
However, applying the classification of creative industries requires a minimum 2-digit disaggregation (ideally 4 or 5 digits).Currently there is no global database with sufficient sector breakdown.In order to elaborate this indicator we used:i) UNESCO’sdatabase of cultural industries, and ii) the core copyright activities of the WIPO-OHIM (hereafter WO) intellectual property databases elaborated by the World Intellectual Property Organization (WIPO and the European Office for Harmonization in the Interior Market (OHIM; see WIPO, 2014; OHIM, 2015)[2].
Both databases have a good number of common sectors (see Table 1). However, the UNESCO indicator focuses on cultural aspects of the creative industries, including manufacture of jewellery and musical instruments, as well as museums activities and operation of historical sites and buildings. On the contrary, the WO indicatorfocuses on industries with the greatest capacity to generate copyright and includes activities such as printing and reproduction of recorded media, computer peripheral equipment and software, or copyright collecting societies. A comparison of the complete list of UNESCO and WO activities is shown in Table 1.
Table 1. UNESCO and WIPO-OHIM creative industries. ISIC Rev.4 codes.
Code / Description / UNESCO2016 / WIPO
and OHIM
Core
1811 / Printing / x
1812 / Service activities related to printing / x
1820 / Reproduction of recorded media / x
3211 / Manufacture of jewellery and related articles / x
3220 / Manufacture of music instruments / x
4649 / Wholesale of other household goods / pc / pc
4651 / Wholesale of computers, computer peripheral equipment, and software / x
4741 / Retail sale of computers, peripheral units, software, etc. / x
4761 / Retail sale of books, newspapers and stationary in specialized stores / x / x
4762 / Retail sale of music and video recordings in specialized stores / x / x
4774 / Retail sale of second-hand goods / pc
5811 / Book publishing / x / x
5812 / Publishing of directories and mailing lists / x
5813 / Publishing of newspapers, journals and periodicals / x / x
5819 / Other publishing activities / x / x
5820 / Software publishing / pc / x
5911 / Motion picture, video and television programme production activities / x / x
5912 / Motion picture, video and television programme post-production activities / x / x
5913 / Motion picture video and television programme distribution activities / x / x
5914 / Motion picture projection activities / x / x
5920 / Sound recording and music publishing activities / x / x
6010 / Radio broadcasting / x / x
6020 / Television programming and broadcasting activities / x / x
6201 / Computer programming activities / x
6202 / Computer consultancy activities / x
6209 / Other information technology and computer service activities / x
6312 / Web portals / x
6391 / News agency activities / x / x
6399 / Other information service activities / x
7110 / Architectural and engineering activities and related technical consultancy / pc
7220 / Research and experimental development on social sciences and humanities / x
7310 / Advertising / pc / x
7320 / Market research and public opinion polling / pc
7410 / Specialized design activities / x / x
7420 / Photographic activities / x / x
7490 / Other professional, scientific, and technical activities / pc
7722 / Renting of video tapes and disks / x / x
7729 / Renting and leasing of other personal and household goods / pc
8219 / Photocopying, document preparation, and other specialized office support activities / x
8299 / Other business support service activities / pc
8530 / Higher education / pc
8542 / Cultural education / x
9000 / Creative, arts and entertainment activities / x / x
9101 / Library and archives activities / x / x
9102 / Museums activities and operation of historical sites and buildings / x
9103 / Botanical and zoological gardens and nature reserves activities / x
9412 / Activities of professional membership organizations (inc. Copyright collecting societies) / pc
* Partial codes (pc)
3.3. Creative industries: The combined UNESCO+and WO+ indicators
The UNESCO database contains information on the percentage of persons employed in cultural industries in 57 countries in 2014. The indicator can be elaborated to includeanother 10 European countries using EUROSTAT data (Structural Business Statistics and Labour Force Survey) and the USA (U.S. Bureau of Labor Statistics), totalling to 67 countries.The WO indicator includes information on the share of core copyright activities in 52 countries between 2011 and 2013. The indicator can be elaborated for anotherseven European countries using EUROSTAT data (Structural Business Statistics and Labour Force Survey), totalling 59 countries.