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.