Gender equality and work–life balance are highlighted in innovation research, as those are directly related to the work environment of R&D personnel. This study empirically explores how scientists’ attitudes valuing gender equality and work–life balance affect their quantitative and qualitative research performance, in basic science. As a result, the more important scientists value gender equality, the better the qualitative performance. Also, scientists who believe that work–life balance is important, produce qualitatively superior research outcomes. However, in the case of quantitative performance, it was not affected by how much scientists value gender equality and work–life balance. This study is a novel attempt to analyse the effect of scientist’s attitude which value gender equality and work–life balance on their research performance.

As digital transformation accelerates worldwide, ICT innovation capabilities are attracting attention as the core competitiveness of companies. However, ICT technologies evolve faster than other technologies, and it is difficult to predict their performance due to high uncertainty in terms of innovation characteristics. This study uses machine learning methods to predict ICT business process innovation performance and derives variables that most importantly affect performance prediction. This study used data from the 2020 Korea Innovation Survey. The main result was that the random forest model accurately predicted the ICT business process innovation performance. Among the four explanatory variables, information sources were the most critical factor in predicting innovation performance. This study provides several implications. First, it contributed to the research of technology forecasting by presenting a machine learning model that can accurately predict ICT innovation performance. Second, this study suggests that managers should actively utilise external information to engage in ICT innovation.

This study investigates the effect of corporate R&D investment on the asymmetric behaviour of SG&A costs. Managers decide how much resources to invest in R&D, based on the strategic objectives of the company. We found that if more resources are invested in R&D, the company reserves more resources when sales decrease. Additionally, we distinguished capitalised R&D from expensed R&D to demonstrate that the effect on SG&A cost behaviour is different according to disclosure policies. This will help in understanding the decision-making process which is dependent on the management’s motivation or perception of R&D investment.

Researchers are highly interested in research data management to derive excellent research results. This study analyzes the determinants affecting the acceptance of blockchain-based electronic lab notebooks service as research data management service. A research model was established based on the technology acceptance model. The sample is collected by 585 researchers from universities and research institutes in Korea. The main research results showed that the usefulness and ease of use lowered the perceived risk and increased the intention to use. Social norms also decreased perceived risk factors and increased intention to use. Research implications are that managers should seek ways to lower the technical risks of blockchain when developing blockchain-based services. In addition, they have to allow users to easily use blockchain-based services and recommend them to other users around them.

SMEs need to protect their innovation outcomes and increase profits from their innovations in order to make their growth sustainable. The appropriability regime enables SMEs to secure financial returns on their R&D investment so that SMEs can continuously invest in innovation and obtain financial gains. However, the appropriability regime can change the effects of protecting innovation outcomes depending on the capacity of knowledge exploration, especially for SMEs, and previous studies have not discussed these issues. Thus, the main objective of this paper is to explore how the knowledge exploration capacity affects the relationship between different types of appropriability regimes and innovation performance. Multivariate regression is used to analyze the manufacturing SMEs sampled from the Korea Innovation Survey 2007 (KIS 2007). Our results demonstrate that both formal and informal appropriability regimes can improve firm’s innovation performance. Furthermore, although both inventive and absorptive capacity have positive moderating effects on the relationship between the informal appropriability regime and innovation performance, the inventive capacity moderates negatively the relationship between the formal appropriability regime and innovation performance. As a whole, the significance of this paper lies in providing further understanding of the different types of appropriability regimes and knowledge exploration capacity in SMEs.