Context:
The EU faces structural challenges compounded by the recent economic crisis. More and better jobs are needed to lower unemployment, raise employment participation rates, and tackle social exclusion and inequality. The Europe 2020 growth strategy wants smart, sustainable and inclusive growth, with innovation and job quality as flagship initiatives. Questions arise about innovation's impact on the number and quality of jobs. Research on the mutual impact of innovation and job quality and mechanisms whereby this takes place is needed.
Objectives:
QuInnE contributes to the EU growth agenda by exploring the mutual relationship between innovation and job quality and identifying mechanisms leading to more and better jobs, and actions to help tackle social exclusion and inequality. QuInnE delivers:
1. new scientific understanding of the innovation-job quality-employment dynamic;
2. new diagnostic and developmental tools to help monitor and measure this dynamic and improve practice in firms;
3. evidence-based advice for policy.
Results:
Policy analysis findings:
Despite an evolution in EU and member states’ innovation policy from a narrow towards a broader conception of innovation, innovation policy still primarily privileges an R&D and Science and Technology (STI) orientation, with deficient recognition of smaller, incremental, and non-technological innovation. The latter have an underappreciated value per se, and in supporting other types of innovation. When the broad conception of innovation is recognized in declarative policy statements, an overwhelming return to the STI perspective occurs when measurement and action plans are created. A very uneven level of policy learning across the EU is also documented.
Quantitative Findings:
Innovation and the QuInnE job quality indicators correlate, with longitudinal data analysis indicating a causal relationship. The strongest correlations are with product, followed by process innovation. Organizational innovation correlates weaker, likely due to the “organizational innovation” concept containing heterogenous elements. Innovation was found to increase employment levels, even process and organizational innovations, which generally are regarded as oriented towards labour rationalization and thereby job destruction. The studies support the “skill-biased technological change” thesis, that posits that technological change and innovation leads to more higher skilled jobs but not lower-skilled jobs. Thus, innovation tends to increase inequalities between the higher and lower skilled by creating more high-skill, high quality jobs, exacerbating inequality.
Qualitative Findings:
58 case studies were carried out as summarized in Table 3.
Despite some industry and national/institutional specificity, several common processes were found: 1.Rather than technological determinism, firm, managerial and to an extent worker choice played a large role in which innovations were developed or adopted, as well as when, how, and upon whom innovations were applied. 2. The operation of virtuous circles where innovations improved job quality and job quality positively impacts the generation and/or adoption of innovations, and vicious circles where the opposite obtained were analysed. Central to the virtuous circles was management's investment in employees’ innovative capacity, whereas cost-cutting and deskilling characterized vicious circles. 3. Over-optimism about the ability to efficiently automate led to negative consequences in terms of overinvestment in automation technologies and underinvestment in employee recruitment, development and education, leading to qualified labor shortages. 4. Regarding inclusion and inequality, the use of advanced technologies often led to more males, younger, and recently credentialed workers, at the expense of women, older, lower-skilled and workers with older credentials. 5. With regard to social inclusion, only two (both public sector) organisations had active programs to promote inclusion of immigrants, youth, older and less-skilled workers.
Theoretical elaboration:
Significant theoretical elaboration gains have been made in: a) the development of a six-dimensional framework for investigating and monitoring job quality (see Table 4.); and b) the intra-firm dynamics around innovation-conducive job quality and the operation of the virtuous and vicious circles mentioned above. Both the job quality framework and innovation-conducive job quality are discussed in Working Paper 11.
Improving data
Working Paper 14 is a critical evaluation of the utility of existing surveys and data sets for analyzing the relationship between innovation, job quality and employment, and provides practical suggestions for improving surveys and data sources.