An exploratory review of the relationship between enterprise training and technology upgrading: evidence from South African manufacturing firms

Abstract

The study examines the extent to which disaggregated training variables are related to technological upgrading, in the context of a middle-income developing country trying to manage its integration into the global economy. For a developing country, successful integration into the global economy requires that local manufacturing firms are able to competitively restructure, as a precondition for survival and long-term growth. Consequently, skills and technological upgrading are crucial in raising the international competitive advantage of local firms. Enterprise-provided training is one means that can be used by local firms to continuously upgrade their knowledge bases, increase their international competitiveness, and enhance employment growth over time. This paper uses South Africa as a case study, to demonstrate how economic reform measures can expose skills deficiencies in the manufacturing sector and lead to an increase in capital intensity of the sector. Exposure of skills deficiencies, in turn, raises the importance of skill-upgrading through schooling and training of existing workforce. Despite a couple of studies on the evolution of the labour market in South Africa, no previous research has explicitly examined the relationship between technological upgrading and disaggregated training/learning variables at the firm level. This paper aims to fill that gap by focusing on disaggregated enterprise-based training efforts. The study uses the Human Capital theoretical framework to answer the main research question: Which disaggregated learning variables (i.e., on-the-job or off-the-job training offered to different occupational groups) are significantly associated with technological upgrading? The study raises possible issues of heterogeneity in returns to training offered to different occupational groups in the context of technological-upgrading. On the other hand, technological upgrading may not necessarily always disadvantage all unskilled workers. Possible policy implications of research findings are outlined.

Keywords:

• enterprise training
• globalisation
• learning
• manufacturing
• technology upgrading

Acknowledgements

The authors are grateful for comments made by one anonymous referee on the earlier draft. The views in the paper do not reflect those of the organisations to which the authors are affiliated.

Notes

 1. Even though this paper uses the Human Capital theoretical framework, it does not in any way aim to cover all the various strands of the theory associated with investment in human capital. Only those components that are relevant to this study are covered.

 2. In this paper, on-the-job training and specific training are interchangeable. Similarly, off-the-job training and general training are taken to be the same. Ng (2005) and Xu (2005) take the same assumptions.

 3. The theory predicts that the investment will be ‘jointly shared’ because of the nature of the employment contract for ‘specific’ training. If there is a separation after training, both the employer and the employee will not benefit from returns to such training. Consequently, by jointly investing in specific training, both parties have incentives not to break the employment contract (Sørensen 2000).

 4. Human capital is defined as the total accumulated stock of knowledge, skill, experience and competencies of the workforce (Barrett and O'Connell 2001).

 5. A large firm is defined as a firm with at least 50 full-time employees. However, from the sample of firms that answered the questionnaire, there are a few firms whose employee size just fell below 50.

 6. For more details on the sampling procedure used, see Chandra et al. (2001).

 7. We treat new investment as technological upgrading, as we assume that new vintage capital will be better than old equipment and machinery in several aspects of their operating characteristics (i.e., speed, accuracy of output, complexity of operations that can be handled by the new machines, etc.). Other studies have also used new investment in equipment and machinery to pick-up ‘technological upgrading’. These include Bernard and Jensen (1997), Navaretti, Soloaga and Takacs (2000) and Pavcnik (2003).

 8. In recent years, MNEs in the motor vehicle sectors have been an exception to this observation.

 9. The ‘InterestRateHigh’ variable is a dummy variable. It was extracted from one question which asked whether ‘high interest rates have been a problem or not’. As such, the dummy variable picking the impact of interest rates is weak. Hence, the need to be careful when interpreting this result.

10. The variable ‘WageBltotlRd’ was in fact the total wage bill normalised by total value of machinery and equipment owned by a firm. The average wage per employee variable ‘AvgTWagePerEmpl’ was alternatively used in the second regression equation. The introduction of the ‘average wage per employee’ in place of the ‘total wage bill’ did not change the results of the respective coefficient.

11. Admittedly, this study does not focus on the social cost or implications on unskilled workers who were retrenched due to technological upgrading.