Expected job creation across the cultural industries: a sectoral division and its implications for cultural policy

Abstract

The cultural industries have come to the forefront as the potential job creators of the future. However, building on the concentric circles model and production system view of the cultural industries, we pose that many young and small organizations in the industries lack the motivation, ability, and opportunity to become job creator. We reason that industry location crucially affects job creation expectations. Evidence from an international sample of early-stage entrepreneurs strongly supports this thesis. We identify a divide between entrepreneurs in the ‘core’ cultural industries vis-à-vis those in the ‘non-core’ cultural industries, where the latter group is indistinguishable from entrepreneurs in non-cultural industries in their job creation expectations. Simultaneously, those in the core cultural industries are distinct from others in their expectations to maintain the same number of jobs, rather than grow. These findings have important implications for cultural policy aimed at promoting employment growth in the cultural industries.

Keywords:

• concentric circles
• job creation
• cultural industries
• entrepreneurship
• production system view

Subject classification codes:

• D92
• L26
• J21
• M13
• Z10

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The countries are: Australia; Austria; Belgium; Canada; Czech Republic; Denmark; Finland; France; Germany; Greece; Hong Kong; Iceland; Ireland; Israel; Italy; Japan; the Netherlands; New Zealand; Norway; Portugal; Singapore; Slovenia; South-Korea; Spain; Sweden; Switzerland; Taiwan; Trinidad & Tobago; United Kingdom; United States. In robustness checks, we assessed to what extent our findings may be region-specific (based on region delineations by the United Nations). These checks consistently indicate that our findings are not region-specific. These checks are available upon request.

2. We calculate the expected percentage growth (job creation expectations divided by the current number of employees and owners) and remove those in the top 1% of the distribution. Similarly, we exclude ventures in the top 1% of the size distribution. All results are robust to the inclusion of these outliers (available upon request).

3. Probabilities that the outcome will take on either the value −1, 0, or 1 are computed as: $\left[1-e^{\left({\mathit{\alpha }}_{\text{a}}+X_{\text{i}}{\mathit{\beta }}_{\text{a}}\right)}/\left(1+e^{\left({\mathit{\alpha }}_{\text{a}}+X_{\text{i}}{\mathit{\beta }}_{\text{a}}\right)}\right)\right]$; $\left[e^{\left({\mathit{\alpha }}_{\text{a}}+X_{\text{i}}{\mathit{\beta }}_{\text{a}}\right)}/\left(1+e^{\left({\mathit{\alpha }}_{\text{a}}+X_{\text{i}}{\mathit{\beta }}_{\text{a}}\right)}\right)-e^{\left({\mathit{\alpha }}_{\text{b}}+X_{\text{i}}{\mathit{\beta }}_{\text{b}}\right)}/\left(1+e^{\left({\mathit{\alpha }}_{\text{b}}+X_{\text{i}}{\mathit{\beta }}_{\text{b}}\right)}\right)\right]$; and $e^{\left({\mathit{\alpha }}_{\text{b}}+X_{\text{i}}{\mathit{\beta }}_{\text{b}}\right)}/\left(1+e^{\left({\mathit{\alpha }}_{\text{b}}+X_{\text{i}}{\mathit{\beta }}_{\text{b}}\right)}\right)$, respectively. That is, in computing the probability that the respondent expects to become a job destructor, only the coefficients denoted as α _a and β _a above are used; for the probability that the respondent expects to become a job creator only the coefficients denoted as α _b and β _b are used. Both sets of coefficients are used for the probability that the respondent expects to become a job maintainer.

4. We take applied creativity to be both the application of others’ creativity, as in the publishing industry, and the application of one’s own creativity to the demand of others, as in the advertising industry.

5. We thank an anonymous reviewer for this suggestion.