How do employee training and knowledge stocks affect product innovation?

ABSTRACT

The main purpose of this paper is to explore how interactions of knowledge flows and knowledge stocks could shape firms’ innovative performance. Knowledge flows are measured on the grounds of human resource training practices while different levels and forms of knowledge stocks (i.e. educational attainment, exporting activity, and firm age) are considered. We make use of two-period panel probit regressions and a rich data survey of the 524 largest Greek manufacturing firms conducted in two waves (2011 and 2013). Our findings suggest that the beneficial effects of knowledge flows strengthen when knowledge stocks accumulated by employees’ education and firm age are low. When knowledge stocks are limited, knowledge flows can act as a bridge for product innovation. On the contrary, when knowledge stocks are high, higher investments in knowledge flows may lead to diminishing returns and, thus, to decreased innovation performance beyond a certain point.

KEYWORDS:

• Training
• product innovation
• knowledge flows
• knowledge stocks

JEL CODES:

• M53
• O30
• O32

Acknowledgements

Thanks are due to the editor and two anonymous referees, for their useful and insightful comments. In addition, we wish to thank the Foundation for Economic and Industrial Research as well as the Laboratory of Industrial and Energy Economics at the National Technical University of Athens for providing us with the survey data used in our research.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. González, Miles-Touya, and Pazó (2016) highlight that within the literature on innovation determinants at the firm level, the majority of the empirical works focuses on the role that R&D plays in shaping innovation.

2. Only a few studies provide mixed evidence for the existence of both significant and insignificant linkages between employee training and product innovation depending on the innovation indicator used (Arvanitis, Seliger, and Stucki 2016) and the size group examined (González, Miles-Touya, and Pazó 2016), as discussed in more detail in the introduction section.

3. A number of studies provide evidence that firms’ innovative activities may be depend on learning effects, allowing for them to improve their innovative capabilities over time (Stein 1997; Sagar and van der Zwaan 2006).

4. However, the story about the impact of firm age on product innovation can take as well the other way round (Balasubramanian and Lee 2008; Zhou, Dekker, and Kleinknecht 2011), since young firms exhibit a more flexible management being thus less resistant towards new and innovative ideas compared to older firms (Dirks and Ferrin 2001; Maurer 2010). A few studies find a negative effect of firm age on product innovation (e.g. Hansen 1992). On the other hand, some studies seem to suggest the existence of a positive relationship between product innovation and firm age. For example, Zhou, Dekker, and Kleinknecht (2011) provide evidence (at the 10% level) that older firms might have higher new product sales compared to younger firms when considering the total sample. However, in the context of our analysis in which firm age is considered as a proxy for knowledge stock, we expect a positive relationship between firm age and innovation output.

5. The rest of the sample was replaced by other firms reporting similar characteristics in terms of employment and sales.

6. According to the Global Competitiveness Report 2016–2017 (WEF 2016), the extent of staff training in Greece (indicator 5.08) has increased gradually from 2010 onwards. In this recent report Greece ranks at the 75th place, which is the highest ranking during the crisis years. This positive trend may be a result of additional funding that was made available from NSRF funds from the European Commission. The European Economic Recovery Plan, proposed by the Commission in November 2008, focused on activation measures, re-training and skills upgrading so to promote further employability of workers (European Commission 2008). As part of this plan, the Commission has launched a major European employment support initiative, whose aims include simplifying the criteria for European Social Fund support and stepping up advance payments. Greece took advantage of these activation schemes, although with significant delay at late 2011 (Hellenic Republic – Ministry for Development & Competitiveness 2014).

7. If this firm is considered as an outlier and is omitted from the descriptive calculations then the average size is 116 (in 2013) and 134 (in 2011).

8. More specifically, the examined firms are classified in nine sectors: Food and Beverages, Textile, Paper and Publishing, Chemical products, Plastic/ Elastic Industry, Non metallic Industry, Basic metals, Machine and machinery equipment, Furniture, and Rest of manufacturing sectors.

9. The results from two-period panel logit regressions we performed as a robustness check are in the same direction. The relevant results are available upon request from the authors.

Additional information

Funding

The two surveys were carried out in the context of a wider research project that was funded by the Hellenic Federation of Enterprises (SEV) and was undertaken by the Foundation for Economic and Industrial Research (FEIR/IOBE) and the Laboratory of Industrial and Energy Economics at the National Technical University of Athens.