Abstract
Workplace innovation has attracted increasing attention within Europe both amongst researchers and policy makers. This paper begins by drawing on the results of the 5th European Working Conditions Survey (EWCS) to map different forms of work organisation for the EU-27 and Norway. It then examines at both the individual level and the group or national level the relationships between a measure of process innovation and the use of what are referred to as the ‘discretionary learning’ (DL) forms of work organisation, characterised by high levels of employee learning, problem-solving and discretion in work. The results point to a systemic relation at the level of national innovation systems between the frequency of process innovations and the frequency of the DL forms. This is explained in part by the way the DL forms provide employees with opportunities for the exploration of new knowledge that can result in new process innovations that diffuse beyond the firm’s boundaries. The paper then proceeds to address the issue of labour market policies for promoting the adoption of the DL forms. It presents evidence to show that the likelihood of the DL forms is higher in nations with more developed systems of ‘flexible security’ characterised by high levels of labour market mobility, unemployment protection and active labour market measures.
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Notes
For a fuller discussion of these points, see Lorenz (2013)).
Surveys carried out in Sweden and Norway at the employer level used the same sample frames as those used for the CIS surveys in these countries which allow for an exploration the interdependencies between CIS-based measures of product and process innovation and measures of work organisation and organisational design. Similar analyses can be undertaken with the Finnish and Danish surveys that are linked and include CIS-based measures of product and process innovation in the employer-level survey. For an overview of the results of the linked Finnish survey, see http://www.tekes.fi/en/whats-going-on/news-2013/liideri/finnish-companies-implementing-a-great-number-of-changes/. For an edited volume of studies based on the Swedish Meadow survey, see Hagen (2011).
For the master questionnaire in English, see http://www.eurofound.europa.eu/surveys/ewcs/2010/documents/masterquestionnaire.pdf
The interviews were carried out between 23 January and 27 June 2010. The target number of interviews was 1000 except in Slovakia, the UK, Italy and Poland (1500), Germany (2000), France (3000) and Belgium (4000). See Parent-Thirion et al. (2012)
The factor analysis method used here is multiple correspondence analysis (MCA) which is suitable for the analysis of categorical variables (Greenacre, 1993, pp. 24–31). The clustering is performed on the factor scores of the first three factors of the MCA which combined account for slightly over 40% of the total variation in the data set.
In order to assure the representativeness of the results for workers in Europe, three types of weights are used for calculating frequencies and in carrying out the different econometric analyses in this paper: a selection probability weight to adjust for the fact that people in households with fewer persons have a greater chance of being interviewed; a post stratification weight to adjust for the overrepresentation of groups with regard to gender, age, region, occupation and sector of activity; and a supra-national weight to adjust for differences in the size of nations. The supra-national weights should be applied for all analyses carried out at the European level. See Parent-Thirion et al. (2012, pp. 146–47).
See Table 15 for the survey questions upon which the work organisation variables are based.
See Holm and Lorenz (2013) for an analysis the time trend in the forms of work organisation based on a cluster analysis using the pooled data for the 2000, 2005 and 2010 waves of the EWCS.
Bulgaria is an outlier in each of the four scatter plot diagrams. While the values of the R-squared statistic change in the correlations that exclude Bulgaria, the basic interpretation remains the same. Excluding Bulgaria results in a decline in the R-squared in the cases of DL (R-squared = .22), Taylor (R-squared = .21) and Simple (R-squared = .28). The value of the R-squared increases from .00 to .05 in the case of Lean.
The odds ratios for nation dummies are presented in the ‘Appendix’.
The inclusion of country-level variables should help to account for some of the unexplained variance in the intercept term in a random intercepts model. See Rasbash et al. (2005).
See Alasoini et al. (2005) for an overview.
Labour market policy measures cover interventions which aim at activating the unemployed, helping people move from involuntary inactivity into employment or maintaining the jobs of persons threatened by unemployment. They include measures in the form of training, job rotation and job sharing, employment incentives, direct job creation and start-up incentives. LMP Supports include out-of-work income maintenance and early retirement. LMP Services cover activities of publicly funded services for jobseekers. See http://epp.eurostat.ec.europa.eu/cache/ITY_SDDS/en/lmp_esms.htm
Source: Eurostat, Data in Focus, No. 35/2009. Mobility figures are for the first quarter of 2009 with the exception of Malta and Luxembourg which are for the fourth quarter of 2008. As the figures for the Netherlands are unreliable, I have used Stata’s impute procedure to estimate the value on the basis of the values for the other five labour market variables.
Factor analysis was carried out using the principal components factor method. Orthogonal rotation was performed on the first three factors each with eigenvalues greater than one. The uniquenesses of the original variables are uniformly less than 0.24
The factors have been standardised to have mean 0 and standard deviation 1.
More concretely this means, other things equal, that the odds of innovation for employees on average in Denmark, the nation with the highest score on the flexible security scale, are about 80 % higher than the odds for employees in general in Poland, the nation with the lowest score.
In order to allow a comparison of the size of the effects at the country-level; the labour market context variables and the share of DL have been standardized to have mean 1 and standard deviation 0.
The LR test performed on model 18 shows no statistically significant improvement in the fit compared to model 17. This is consistent with the spirit of the mediation analysis since it shows that the inclusion of the DL share rather than improving the fit of the model substitutes for the flexible security scale in accounting for the odds of process innovation.
See Alasoini et al. (2005) for an overview.
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Appendix
Appendix
Work Organisation Variables
Survey questions and frequencies of indicators | |
Team work: Does your job involve doing all or part of your work in a team? | 63.4 |
Job rotation: Does your job involve rotating tasks between yourself and colleagues? | 49.0 |
Quality norms: Does your main paid job involve meeting precise quality standards? | 77.5 |
Discretion in fixing work methods: Are you are able or not to choose or change your methods of work? | 58.2 |
Discretion in setting work pace: Are you are able or not to choose or change your pace of work? | 61.2 |
Horizontal constraints on work pace: On the whole, is your pace of work dependent or not on the work of your colleagues? | 49.0 |
Hierarchical constraints on work pace: On the whole is your pace of work dependent or not on the direct control of your boss, | 44.5 |
Norm-based constraints on work pace: On the whole your is your pace of work dependent or not on numerical production targets? | 53.4 |
Automatic constraints on work pace: On the whole is your pace of work dependent or not on the automatic speed of a machine or movement of a product? | 26.6 |
Employee responsibility for quality control: Does your main paid job involve assessing yourself the quality of your work? | 71.2 |
Employee problem-solving: Does your main paid job involve solving unforeseen problems on your own? | 80.2 |
Learning new things: Does your main paid job involve learning new things on your own? | 66.0 |
Task Complexity: Does your main paid job involve complex tasks? | 60.0 |
Task monotony: Does your main paid job involve monotonous tasks? | 48.7 |
Task repetitiveness: Does your job involve short repetitive tasks of less than one minute? | 30.6 |
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Lorenz, E. Work Organisation, Forms of Employee Learning and Labour Market Structure: Accounting for International Differences in Workplace Innovation. J Knowl Econ 6, 437–466 (2015). https://doi.org/10.1007/s13132-014-0233-4
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DOI: https://doi.org/10.1007/s13132-014-0233-4