Hyoung Sun Yoo

Gender diversity among inventors has been on an increasing trend, yet prior evidence on the gender diversity–innovation link at the firm level is somewhat mixed. We argue that this inconsistency is due partly to a compositional focus that overlooks how inventors actually collaborate inside firms. In this regard, we distinguish gender diversity (who is present) from the structure of intrafirm collaboration (who collaborates with whom) by introducing gender assortativity as a network-level indicator of cross-gender segregation versus mixing. Then, building on a recombinant view of innovation, we reconcile competing arguments on gender configuration and innovation by suggesting that, while composition creates potentials for benefits and costs associated with knowledge recombination, collaboration structure governs the realization of the potentials. Using a panel of U.S. firms, we examine how gender assortativity relates to firm innovation performance and how the relationship varies with gender diversity. We find an inverted U-shaped relationship: innovation performance peaks at moderate gender assortativity, while both highly gender-segregated and intensive cross-gender mixing structures are associated with lower performance. Further, the curvature of the inverted U-shaped relationship is muted in networks with low gender diversity, but becomes salient in intermediate- and high-diversity regimes. In doing so, this study highlights the need for complementing headcount diversity metrics with network diagnostics, which leads to several theoretical and managerial implications.

Purpose: This study investigates the effects of related and unrelated technology diversity on R&D efficiency and how a firm’s unique core technology moderates this relationship. In particular, this study aims to address the research gap in the technological diversity literature by examining whether the effects of related and unrelated technological diversity on R&D efficiency are consistent in the context of R&D-intensive firms.Design/methodology/approach: Using a panel dataset of 516 top R&D investors worldwide from 2012 to 2018, the paper tests hypotheses on how the ambivalence of technological diversity affects R&D efficiency depending on the level of diversity.Findings: Unrelated technological diversity has an inverted U-shaped curve relationship with R&D efficiency, which indicates that there exists an optimal point of unrelated technological diversity. Additionally, core technology plays a contingent role in this relationship by alleviating the volatility of the inverted U-shaped relationship between unrelated technological diversity and R&D efficiency.Originality/value: This study makes an original contribution to the technological diversity literature by adopting an approach not limited to specific countries or industries, focusing on R&D-intensive contexts. Furthermore, the paper distinguishes the various types of technological diversity, considering that the motivations and strategic objectives underlying technological diversity vary depending on the specific type. This allows researchers to gain a deeper insight into how different types of diversity strategies impact R&D efficiency.

While the cases of small and medium enterprises (SMEs) that succeeded in research and development (R&D) have been relatively well known and studied, there has not been sufficient research on cases of R&D failure and the consequent costs. Based upon the resource-based view, we hypothesized that commercialization failure of SME's R&D would be more severe for smaller firms lacking resources and dynamic capabilities, leading to early business closure. We analyzed 2,038 formal R&D projects implemented by South Korean SMEs with the support of a public subsidy program. We found that if an SME that implemented the R&D project failed to commercialize the outcomes of the R&D, the probability of business closure within 5 years after the completion of the project is 72% higher than if it succeeded. We also found that the commercialization failure increases the risk of business closure, particularly for smaller firms, due to a significant slowdown in sales growth. Our findings underscore the importance of the R&D planning strategies for SMEs and the need for funding agencies to improve their program segmentation and beneficiary selecting process.

Despite the growing demand for corporate environmental, social, and governance (ESG) engagement in response to the global complex crisis, the impacts of ESG activities and market environment on firm performance have not been sufficiently investigated. This study aims to explore how ESG activities affect firm performance and how the competitive market environment moderates this relationship. The panel data regression analysis was performed to investigate the relationship between the ESG performance and firm performance (specifically, market capitalization as a measure of market‐based firm performance and profit margin and return on assets as measures of account‐based firm performance) with the data of 2115 listed companies from 53 countries over the past 5 years (2017–2021). The analysis results showed a U‐shaped relation between ESG performance and market capitalization, and a positive linear relationship was observed between ESG performance and profit margin or return on assets. Importantly, it was found that these relationships are negatively moderated by the competition (number of competitors) in the market. It can be interpreted that the greater the number of competitors in the market, the weaker the effect of ESG performance on firm performance. This study discusses plausible reasons for these observations and managerial and policy implications drawn from the results. This study not only analyzes the relationship between ESG performance and various aspects of firm performance at the global level, but also accumulates new evidence for the moderating effect of market competition.

To improve the efficiency of government-funded research and development (R&D) programs for small and medium enterprises, it is necessary to make the process of selecting beneficiary firm objective. We aimed to develop machine learning models to predict the performances of individual R&D projects in advance, and to present an objective method that can be utilized in the project selection. We trained our models on data from 1771 R&D projects conducted in South Korea between 2011 and 2015. The models predict the likelihood of R&D success, commercialization, and patent applications within 5 years of project completion. Key factors for predicting the performances include the research period and area, the ratio of subsidy to research budget, the firm’s region and venture certification, and the average debt ratio of the industry. Our models’ precisions were superior to qualitative expert evaluation, and the machine learning rules could be explained theoretically. We presented a methodology for objectively scoring new R&D projects based on their propensity scores of achieving the performances and balancing them with expert evaluation scores. Our methodology is expected to contribute to improving the efficiency of R&D investment by supplementing qualitative expert evaluation and selecting projects with a high probability of success.

Although there has been a lot of research on the effect of workforce diversity on innovation performance, the studies on research and development (R&D) team diversity have been scarce. Moreover, even the previous studies considered R&D performances at the firm level, which left the relationship between inputs and outputs unclear. This study aimed to investigate the relationship more precisely by examining the effect of R&D team diversity at the project level. The gender, major, and education diversities were considered and the project‐level performances were measured by four indicators: papers, patents, R&D success, and innovative sales. After analyzing 1166 R&D projects implemented by South Korean small and medium‐sized enterprises supported by government subsidies, we found inverted U‐shaped relationships between gender and major diversities and patent applications. That is, patents increased from low to moderate level of diversities (0.52 for gender diversity and 0.43 for major diversity in normalized Blau's index). However, when the diversities exceeded the moderate levels, patents decreased. Our findings provide strong empirical evidence that the ambivalence of diversity influences simultaneously and that the influences dominate differently depending on the degree of diversity. Education diversity had a linear positive correlation with paper publications and R&D success. Based on these findings, we discussed managerial implications from the perspective of R&D project managers and the funding agency.

Despite a long period of research on the relationship between competition and innovation, contradictory observations about their relationship have been reported and there is yet no consensus on this relationship. Moreover, there have been few studies on how this relationship is affected by the characteristics of companies participating in the market. In this article, we aim to examine the relationship between competition and innovation activities, particularly in the pharmaceutical industry, and investigate how this relationship is moderated by the size and age of leading companies. By analyzing 8243 reported drug development activities and the competitive intensity of the global pharmaceutical market for 234 drug classes, we found that there is a positive linear relationship between the 1-Herfindal–Hershman Index or the number of competitors and the number of drug development projects. In addition, it was found that this relationship is negatively moderated by the size and age of the leading participating companies. Based on these findings, we discussed several implications for stimulating pharmaceutical innovations.

At a time when the COVID-19 pandemic has been ongoing for more than a year, young people have been the subject of vigilant scrutiny and criticism regarding their active engagement in social activities. We posed the question of whether young people's response to COVID-19 was different from that of other generations and analyzed awareness and behavior to investigate this question. Specifically, we examined internet searches for information on COVID-19 and credit card consumption in South Korea among young people in their 20s and compared them to a reference group of people in their 50s. Our research has confirmed that there was no statistically significant difference between young people and the reference group in this regard. Furthermore, in the 25 sub-sectors of industry we examined, young people's consumption activities recovered significantly faster than the reference group in only three sub-sectors. This study demonstrated that young people showed stronger interest than the reference group in their response to COVID-19, and that they cooperated with the government’s social distancing policy by reducing their activities. Through this study, we presented a scientific approach for evaluating young people in regard to their response to COVID-19, offering useful implications for designing appropriate policies for public health.