Issues and aims in our project

2.1 Difference between mobility and fixed-term employment

As we already noted above in the section briefly analysing the job-to-job mobility data the patterns found in our three study-countries points to the need of building on a theoretical model or models that can help us understand the specific factors leading to a change in jobs for young women in the ICT sector. Labour market models: segmentation, explanations of mobility and in particular of those in ICT sectors who are low paid, etc. can be used to find a correct balance that covers the objectives of our project.

The very brief analysis of the mobility rates above indicates the importance of having a clear model taking into account the push and pull factors behind the mobility decision including personal, cultural and institutional factors and in a given labour market context, in particular different flexibility patterns and firm organisational issues. These factors will have different effects on women and men that must be taken into account. Although there is a great number of job-to-job mobility literature by economists and sociologists (we are sending our literature search to ITC/ILO) there are few specific analysis of the gender dimensions. Curiously there are many analyses for job-to-job mobility of young men and most of the studies are centred on how this affects individual wages: the theory is that young people move frequently during their first years in paid work in order to get better conditions, especially wages.

There are fewer studies on the impact on firms, but in general it is accepted that high turnover rates are costly and inefficient for firms, and that workers with more experience from other sector or from the same sector are an asset to the firm. However, in the knowledge economy it has also been shown that knowledge is an asset of the worker, not the firm and that this leads to different ways of training as well as different recruitment and retention practices. Also, mobility is associated with economic cycles: during low unemployment periods, as wages theoretically rise, workers decide to change jobs; while during high unemployment periods workers tend to stay put. Although these are very general trends, separate trends for women and men are not usually analysed. In principle, during high unemployment periods women’s activity rates rise as men become workless (they are more active searching for jobs, but not necessarily find them and if they do they tend to be low paid jobs).

The work by Cappellari22 also points to the difficulties of low wage workers affected by high mobility which does not increase their chances of finding higher paying jobs, i.e. a low-wage trap results as the more time a low-paid worker remains in low paid jobs the harder it will be to transit to higher paying jobs. On the other hand Tidjens23 has found that a large proportion of persons with low educational levels and minor users of ICT in fact carry out tasks demanding a high educational and professional competency level.

Finally, specific sector effects must also be taken into account as specific labour market surpluses or shortages of workers can also explain mobility as workers identify opportunities for improving their conditions, especially wages, and firms can engage in stealing workers from other firms (so-called tight labour markets). In the case of the ICT sector in the three countries included in our project there can be strong differences in how these specific labour markets work given the differences in institutions and firm culture and the ways how women interact in these markets. We have tried to expound on these differences in the section above dealing with cultural and institutional aspects that were mentioned in the study based on the Eurobarometer on mobility. In addition off-shoring or relocation can also be used by firms affecting the number and the quality of jobs with different outcomes for women and for men.