The effectiveness of public subsidy on innovation and subcontracting regimes in Korean manufacturing SMEs

ABSTRACT

The objective of this study is to verify whether the additionality effect of the public subsidy varies depending on the nature of subcontracting regimes in which manufacturing Small and medium-sized enterprises (SMEs) are subcontracted to large firms. This study adopted the propensity score matching method using inverse probability weights to estimate the average treatment effect on the treated. This research found that the effects of the public subsidy on the input, behavioural, and output additionality varies depending on the subcontracting regimes in manufacturing SMEs. This study also shows that the lower the hierarchical position within subcontracting regimes the more effects of the public subsidy on the input and output additionality are reduced, signalling that the lower the hierarchy of the subcontracting regimes, the less the effectiveness of public subsidy in promoting innovation of SMEs. The results imply that the position of SMEs embedded in subcontracting regimes needs to be considered to mitigate factors that inhibit innovation to correct market failures and improve the knowledge spillover. Further, this study suggests that SMEs need to establish the optimal innovation strategy that can leverage their capability and resource dependence with consideration of their position in the subcontracting regimes.

KEYWORDS:

• Public subsidy
• subcontracting regimes
• additionalities
• manufacturing SMEs
• inverse probability weights

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The number of unique firms that exist in the 7217 observations in total was 3,952, meaning that the 3,265 observations were from firms that surveyed at least two or more times in five years of the whole period of this study. Although the surveys of KVBA used the stratified random sampling method each year, these coincidences can influence the proper estimation of standard errors. Therefore, this study used the clustered standard errors using the unique identifiers to allow for intragroup correlation and account for heteroskedasticity across clusters of observations.

Additional information

Funding

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-A2019-0460).

Notes on contributors

KonShik Kim

KonShik Kim is a lecturer at Kookmin University in Korea. He graduated with a doctoral degree from the Seoul National University of Science and Technology. He holds an MBA degree from KAIST. His research interests focus on management of innovation and business ecosystem based on complexity theory.