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H2020

QuInnE Report Summary

Project ID: 649497
Funded under: H2020-EU.3.6.

Periodic Reporting for period 1 - QuInnE (Quality of Jobs and Innovation Generated Employment Outcomes)

Reporting period: 2015-04-01 to 2016-03-31

Summary of the context and overall objectives of the project

Context:
The EU is facing long-term structural challenges compounded by the recent economic crisis. More and better jobs are needed to lower unemployment, raise the employment participation rates of female, older, migrant, low-skilled and young workers and thus tackle social exclusion and inequality. The EU’s growth strategy, Europe 2020, wants smart, sustainable and inclusive growth, with innovation and job quality as flagship initiatives to meet these growth objectives. Innovation and job quality are however currently treated separately but ought to be better integrated in policy and workplace practice. In previous research a correlation has been found between job quality and innovation. However, research that can elaborate the mutual impact of innovation and job quality and the mechanisms whereby this takes place and thereby displays how they can be levered to mutually boost each other is needed.

Overall objectives of QuInnE:
QuInnE’s primary objective is to contribute to the EU growth strategy of boosting innovation, job quality and employment by exploring the mutually reinforcing relationship between innovation and job quality and identifying mechanisms that can be accelerated to deliver both more and better jobs, which in turn help tackle social exclusion and inequality.

QuInnE creates a new analytical framework of for understanding the relationship between innovation and job quality and that relationship’s impact on employment. This framework is then used to statistically analyse existing datasets to create a typology of innovation-job quality dynamics by industry and country. The analysis is then extended to assess how different types of relationships create jobs, and provide jobs that are accessible and sustainable for groups of workers currently struggling in the labour market, and reduce social inequalities by age, class and gender. QuInnE then explores how the innovation-job quality dynamic can create more and better jobs at firm level.

The three main general outcomes that QuInnE will deliver are:
1. new scientific understanding of the innovation-job quality-employment dynamic;
2. new diagnostic and developmental tools to help monitor and measure this dynamic at national level and improve that dynamic in firms and workplaces;
3. evidence-based advice on developing policy to boost EU growth.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The work performed on the project can be categorized under three headings: 1) scientific work; 2) stakeholder consultation and dissemination; and 3) project management and coordination.

1) Scientific work

As a more detailed description of the most significant scientific advances accomplished by the project is presented in the section below on “progress beyond the state of the art,” a brief overview of the scientific work conducted will be presented here.

The scientific work has progressed in four areas: Quantitative analysis of the relationship between innovation and various job quality indicators and employment effects (WP5); Policy analysis (WP4); Theoretical elaboration of the parameters of and relations between various dimensions of job quality, innovation and employment (the so-called Integrative Framework – WP3); and Preparatory work for the Qualitative analysis (WP6).


Work Package 5 – Quantitative Analysis.
Using existing statistics from the Labour Force Survey and European Working Conditions Survey ( plus the Structure of Earnings Survey and European Statistics on Accidents at Work) for job quality indicators and the Community Innovation Survey and the European Working Conditions Survey for innovation indicators and other Eurostat data for general indicators, Work Package 5 has analyzed the relationships between a variety of job quality variables and innovation at different levels – the EU level, country level, 1-digit industry level and 2-digit industry level. The same work package has also analyzed the relationship between job quality and a number of employment variables. The work carried out has rendered both material for externally oriented scientific publications (due in the next reporting period) as well as necessary inputs to internal compound analytical processes. Under the reporting period, the latter have fed into the work on the integrative framework (WP3) and industry selection in WP6 (D 5.1). The externally oriented scientific publications that the work undertaken by WP5 are:

• D 5.2 (due month 18) Working Paper on industry and cross-country correlations between innovation, job quality, employment and social inclusion and equality.
• D5.3 (due month 20) Working Paper on the relationship between job quality/labour market regimes and innovation regimes.

The main results, based on the analyses carried out by WP5, are summarized in the tables attached below as Image 1 and Image 2.


Work Package 4 – Policy Analysis.
In terms of policy analysis, Work Package 4 has produced two working papers, Innovation policy review: National and European Experiences (Working Paper 1, deliverable 4.1) and The Evolution of EU Innovation Policy Relevant to Job Quality and Employment (Working Paper 2, deliverable 4.2). These working papers have been oriented at the national and EU levels respectively, with a primary focus on innovation policies but a particular interest in if, when and how aspects of employment and job quality policy figure into innovation policies at these two levels. The basic finding is that despite formulations and statements in some national and EU innovation policy documents that seek to transcend the predominant linear, radical and science, engineering and technology innovation paradigm, this is still the primary paradigm in policy formulation as well as (or especially) in concrete policy measures. A second finding is that while the impetus behind innovation policy is economic competitiveness and growth, and a subsequent hope or understanding that this should result in employment growth, the mutually generative relationships between innovation, job quality factors and employment outcomes are seldom acknowledged or specified. Not surprisingly, the national and EU policies reviewed almost exclusively (with some Nordic exceptions to this) focus on external inputs into organizations, rather than organizational internal processes. One conclusion from The Evolution of EU Innovation Pol

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Progress beyond the state of the art has been made in three areas: 1) benchmarking and comparing innovation policy in the seven participant countries and the EU; 2) quantitative analyses of the correlation between innovation and job quality variables; and 3) the development of an integrative framework of analysis for analyzing the mutually generative relationship between job quality and its effects on employment.

1) Benchmarking and comparing innovation policy in the seven participant countries and the EU

With regard to benchmarking and comparing innovation policy, movement beyond the state of the art has been made by explicitly comparing the innovation policies of countries from three of the four EU innovation clusters as elaborated in the 2013 Innovation Union Scoreboard’s Summary Innovation Index (none of the countries in QuInnE are in the Modest innovators cluster). Another advance is in looking for explicit links between innovation policy and two other policy fields – job quality and employment. While connections between innovation and employment are commonly stated, direct relationships between these two fields in terms of policy interlinkages are not articulated, and connections between innovation and job quality are absent in explicit terms, except in the assertion that there is no contradiction or mutually excluding relationship between more jobs and better jobs. As mentioned above, a further advance is in terms of framing variables associated with the DUI (Doing, Using, Interacting) and EDI (Employee-driven Innovation) modes of innovation as dimensions of job quality and in extension of this, promoting investigating other dimensions of job quality as central to understanding the preconditions for and effects of the four forms of innovation. In keeping with progressive streams of innovation research, our policy reviews also display the continuing predominance of the more traditional, narrow, STI (Science, Technology, Innovation), linear and radical innovation orientations in national and EU policy, and the necessity of emphasizing organization level factors and processes. The potential and intended impact of these findings is raising awareness in policy circles that innovation policy needs to understand and promote organization-proximate processes and that many of these entail job quality improvements.


2) Quantitative analyses of the correlation between innovation and job quality variables

Quantitative analysis has moved beyond the state of the art in two regards. The first is the production of unique analyses of existing datasets as stand-alone contributions. The quantitative analyses have led to a novel grouping of EU countries in four innovation and four job quality clusters (see Table 1 below). Likewise, industries (at NACE 1 and 2 digit levels – see Table 2 below) have been classified at the EU and national levels in terms of high and low innovation and job quality, rendering a novel four-field table correlation these two dimensions at industry level for the EU15. The second is the manner in which these analyses feed into the propelling the project towards its overarching goal of understanding the relationships between job quality, innovation and employment. This contribution takes two forms – what we know and what we don’t know and cannot find out via statistical analyses, and thereby become a matter to be investigated qualitatively in WP6.


3) Development of an integrative framework of analysis for analyzing the mutually generative relationship between job quality and its effects on employment

In addition to the above mentioned linking of the three focus areas in terms of mutually generative or recursive mechanisms, the Operational Protocol also explicitly develops a framework for analyzing social inclusion and social equality via employment. Social inclusion is analyzed in terms of attaining and remaining in employment. Here a unique index – the so-called “four S’s” of job types (Ste

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