Choice and allocation characteristics of faculty time in Korea: effects of tenure, research performance, and external shock.

Academics generally should meet both teaching duty and research performance requirements. Since their work time is finite, academics need to allocate time for research, teaching, and other types of work. This means that universities or governments might enhance the efficiency of their faculty systems or educational policies by understanding academics' preferences for choice and allocation of their work time. We analyzed the work time allocation preferences of 450 Korean academics in science and engineering fields based on the multiple discrete-continuous extreme value (MDCEV) model. We classified work time into either of research, teaching, or other tasks and investigated the relationship between academics' preferences in choosing and allocating their work time and faculty system (e.g., tenure), individual characteristics (e.g., research productivity) and external shock (e.g., COVID-19). Analysis results show that academics with either of tenure, higher research productivity, or commercialization experience preferred to allocating their work time firstly to research, i.e., rather than to teaching or other tasks, while this was not the case for the academics after the pandemic. In general, academics appeared not to prefer allocating their work time firstly to teaching. Implications of our study are twofold. First, the higher education sector needs to incentivize academics' teaching time allocation for enhanced effectiveness of education. Second, universities and governments urgently need systems and policies to facilitate academics' research time allocation for enhanced research productivity as we find deteriorated preference for research time allocation after COVID-19.

Economic value of traffic noise reduction depending on residents' annoyance level.

Noise is the most frequently encountered type of environmental pollution in everyday life and has a direct negative effect on humans. Individuals who are constantly exposed to noise tend to have a high incidence of cardiovascular disease and hypertension. Noise sources range from construction sites to political rallies and assemblies, but traffic is one of the most long-lasting and chronic sources of noise. Previously, researchers have conducted valuations of road traffic noise reduction, but they did not consider residents' annoyance levels in response to traffic noise. However, individuals' annoyance levels affect the economic value of noise reduction policies and thus must be considered to obtain an accurate estimate. Therefore, this study investigated residents' willingness to pay for traffic noise reduction depending on their annoyance level. We used the contingent valuation method and a survey to analyze how much 1022 respondents in Korea were willing to pay for noise reduction. We found that people who were annoyed and extremely annoyed by noise had a willingness to pay KRW 8422 (US $7.55) and KRW 9848 (US $8.83) annually per household, respectively, to reduce their annoyance level to zero. In addition, we determined the economic benefits of noise reduction policies using the respondents' willingness to pay to reduce noise by 1 dB(A), which totaled KRW 3.28 billion (US $2.91 million) per year. The results of this study provide estimates of the annual benefits of traffic noise reduction considering residents' annoyance level.

Evolution of technology convergence networks in Korea: Characteristics of temporal changes in R&D according to institution type.

This study investigates the temporal changes in development of technology convergence networks by institution type, i.e., public research institute (PRI), university and industry. Using the co-classification of technological domains of patents, we identified technology convergence of Korean patents, which were filed at Korea Intellectual Properties Office (KIPO) from 1997 to 2011. We conducted a network analysis at the technology level to search for the key technology fields and frequent instances of technology convergence. The results show that technology convergence networks have grown significantly in the recent period regardless of the institution type. While industries started to conspicuously engage in technology convergence in the late 1990s, universities or PRIs did not do so until the mid-2000s. This discrepancy in the phase of technology convergence is attributed to the temporal difference in R&D stage (e.g., basic research and commercial product development). Our findings imply that corporal and governmental R&D management decision on promising technology fields will be more effective if the decision makers carefully consider the type of R&D entity in analyzing technological landscapes.