T4-04: Industrial relations in the digitalised world

6 September 2019, 11:00–12:30

Chair: Werner Nienhüser



Regulating Flexibility

Uber’s platform as a technological work arrangement

Sigurd M. Nordli Oppegaard, Fafo Institute for Labour and Social Research, Oslo

» Full paper: ilera-2019-paper-143-Oppegaard.pdf

The so-called sharing economy is often framed as an adept system for taking advantage of “underutilized” assets and, enabled by digital technology, establishes a community of strangers trusting, interacting and exchanging goods and services with each other. In this article, I explore the “algorithmic management” of Uber’s platform as a technology for organizing the drivers’ labor process based on a case study of Uber Black in Oslo. Within this particular materialization of Uber’s business model, the drivers are employed by limousine companies who own the cars used and endow the drivers with a significant freedom to choose their own schedules. The digital platform used to coordinate the Uber Black market in Oslo, however, is identical to that employed in other countries where Uber provides Uber X or Uber Pop, in which the drivers are self-employed and use their own private cars to transport passengers. According to Uber’s own economists, the flexibility of the Uber drivers formal work arrangement – where the drivers can choose when and how much they want to work – is highly valued by the drivers. But this flexibility is also described as a problem by the same economist: How can the “free” drivers be incentivized to provide their labor when and where Uber needs them to? The answer is the platform, structuring the choices available for the drivers through algorithmic trip assignment, adjustment of the trip fare – and thus the drivers’ earnings – to local fluctuations in supply and demand and the rating system. While the platform can be seen as a “market machine”, institutionalizing market mechanisms to control the drivers’ labor, its techniques for coordinating the market cannot be reduced to price mechanisms alone. I rather argue that the platform should be seen as a privately owned market regulation, parallel to or competing with the governments regulation of the passenger transportation sector depending on the context. In this sense, the platform economy may indicate a transfer of regulatory power from governments to privately owned companies.

Prospects of workers in the automotive industry and social partners responses under new technologies deployment

Monika Martišková, Charles University

New technologies, sometimes referred to as Industry 4.0 technologies, may have disruptive effects on economies, especially in those countries that rely on manufacturing to a large extent. Central and Eastern Europe (CEE) represents a region where the automotive manufacturing has become a crucial segment of the economic growth. The arrival of foreign direct investments solved several difficulties this region had been experiencing in the transition period in the 1990s, such as high unemployment rates, stagnant GPD growth and the lack of available technologies and knowledge. However, new technologies may downscale manufacturing advantages by having strong and mostly negative impact on working conditions and the number of jobs in this sector.

There are at least three main reasons for raising the concerns about the impact of new technologies on working conditions. First, the implementation of new technologies will reduce demand for manual work and decrease wages of manual workers.  Second, because of the labour cost reducing character of technologies, cheap labour, the main competetive advantage of the CEE region, may become obsolete resulting in reallocations either to mother countries or to cheaper locations.  The third concern is related to the quality of working conditions associated with the increasing level of control, deteriorating job stability and decline in complexity of duties in manufacturing jobs (e.g. the “feeding-machines positions”).

The present paper studies the effects of new technologies on working conditions by using an example of automotive industry in Czechia based on the secondary data resources and qualitative interviews conducted in the subsidiaries of multi-national corporations (MNCs) and with representatives of social partners at the sector level in 2018. In the paper it is argued that the new technologies´ expected impact on working conditions, wages or job offers are only partially visible nowadays. This situation is associated with the dependent position of subsidiaries in introducing new technologies in production that stems either from limited competences assigned from the headquarter or from local management limited capabilities to implement new technologies. The economic boom experienced in the CEE countries, including Czechia, provides on the one hand incentives to robots´ utilization because of labour shortage, but at the same time it hampers the new technologies implementation because of the production overload and time and capacities constraints to prepare the changes at the firm level.

In light of this development, social partners are aware of expected changes in working conditions, but at the same time, they remain passive in pushing for measures that would moderate anticipated impacts. A broader concept of economic transition is addressed mostly by the business sector actors while trade unions struggle to be involved in determination of policy instruments that would ensure the smooth transition. One of the most important aspects of successful transformation, workers´ participation on life-long learning, is not promoted neither by the social partners, nor by the government.

In the paper, we discuss the puzzle of current improvements in working conditions and wages and expected massive deterioration of quality and quantity of manufacturing jobs. The prospects of workers in the Czech automotive industry do not seem to be dark for now, but the near future remains to be in question that local actors are not fully capable to answer.

The effects of information and communication technologies on pay for performance use

Alberto Bayo-Moriones, Public University of Navarre
Amaya Erro-Garcés, Public University of Navarre
Fernando Lera-López, Public University of Navarre

» Full paper: ilera-2019-paper-155-Erro-Garces.pdf


Technological change derived from the introduction of information and communication technologies has had substantial consequences in the modern workplace. Among these we could mention their effects on skills, wages, job characteristics and the hierarchical distribution of decision rights (Green, 2012; Bllom et al., 2014).

In this paper we want to analyse the influence of the introduction of computers in the workplace in the adoption of compensation programs that make wages depend on performance at different levels, either the individual, the team or the company. This contributes to the literature on the work implications of ICTs by complementing research on their effects on wages (Dunne et al., 2004).

We also intend to provide some light on the mechanisms through which this potential effect could take place. The main theoretical approaches to the analysis of incentives choice emphasize the role played by work organization as a relevant determinant (Marsden and Belfield, 2010). Therefore, we examine whether the impact of computer technology on pay for performance is mediated by job variables such as complexity or autonomy.

In this line a question that deserves especial attention is whether the influence of computer technology on pay for performance is similar across occupations. Literature on inequality on working and employment conditions has highlighted that the effect of technical change on jobs is dependent on the nature of the tasks, so that the impact differs by occupation (Holman and Rafferty, 2018). For this reason it is relevant to investigate whether the relationship between computers and pay for performance is similar for different occupational groups.


We use data from the last three waves of the European Working Conditions Survey, conducted by the European Foundation for the Improvement of Working and Living Conditions. Therefore, the unit of analysis is the worker. The sample is restricted to employees.

The four dependent variables are binary and capture the use of four pay for performance schemes: piece rate/productivity payments, payments based on the performance of team/department, payments based on the overall performance of the company (for example, profit sharing) and incomes form shares in the company.

The independent variable measures on a 1 to 7 scale the frequency with which the worker uses computer technologies in her job, with 1 indicating she neves uses them and 7 she uses them all the time. The mediating variables include items related to job aspects such as achieving precise quality standars, solving unforeseen problems, complexity, monotony and autonomy.

Since the dependent variables are binary, probit models are estimated. Control variables include country, year, gender age, occupation, industry and firm size. For each dependent variable two models are estimated: the first includes the independent control variables and the second adds the mediating variables.

The analyses are conducted for the whole sample and also by subsamples for non-routine non-manual, routine non-manual, manual non-routine and manual and routine occupations.

Results and Conclusions

We find that there is a positive effect for the whole sample of computer use on the four pay for performance schemes examined. The results also indicate that this effect is partially mediated by the job variables included in the analysis. However, a significant direct effect of computers on pay for performance remains unexplained after controlling for differences in job characteristics.

When estimating the empirical models for the four subsamples defined according to the dimensions routine/non routine and manual/non manual, we find differences in the effects of computers on pay for performance use. This effect is larger for non manual occupations than for manual occupations.

In order to deal with the potential endogeneity of our independent variable, two robustness checks have been conducted. Firstly, multivariate probit models have been estimated in order to allow for correlations between the error terms in the four models estimated. Secondly, instrumental variables models have been performed. Although in some of the models endogeneity problems have been detected, they do not invalidate the conclusion in favor of a positive effect of computers on the use of pay for performance.


  • Bloom, N., Garicano, L., Sadun, R., & Van Reenen, J. (2014): “The Distinct Effects of information Technology and Communication Technology on Firm Organization”, Management Science, 60(12), 2859-2885.
  • Dunne, T., Foster, L., Haltiwanger, J., & Troske, K.R. (2004): “Wage and Productivity Dispersion in United States Manufacturing: The Role of Computer Investment”, Journal of Labor Economics, 22(2), 397-430.
  • Green, F. (2012): “Employee Involvement, Technology and Evolution in Job Skills: A Task-Based Analysis”, Industrial and Labor Relations Review, 65(1), 36-67.
  • Holman, D., & Rafferty, A. (2018): “The Convergence and Divergence of Job Discretion Between Occupations and Institutional Regimes in Europe from 1995 to 2010”, Journal of Management Studies, 55(4), 619-647.
  • Marsden, D., & Belfield, R. (2010): “Institutions and the Management of Human Resources: Incentive Pay Systems in France and Great Britain”, British Journal of Industrial Relations, 48(2), pp. 235-283.


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