The unprecedented outbreaks of epidemics such as the coronavirus has caused major socio-economic changes. To analyze public risk awareness and behavior in response to the outbreak of epidemic diseases, this study focuses on RSV (Relative Search Volume) provided by Google Trends. This study uses the social big data provided by Google RSV to investigate how the WHO's pandemic declaration affected public awareness and behavior. 37 OECD countries were analyzed and clustered according to the degree of reaction to the declaration, and the United States, France and Germany were selected for comparative study. The results of this study statistically confirmed that the pandemic declaration increased public awareness and had the effect of increasing searches for information on COVID-19 by more than 20%. In addition, this rapid rise in RSV also reflected interest in the COVID-19 test and had the effect of inducing individuals to be tested, which helped identify new cases. The significance of this study is that it provided the theoretical foundation for using RSV and its implications to understand and strategically utilize public awareness and behavior in situations where the WHO and governments must launch policies in response to the outbreak of new infectious diseases such as COVID-19.

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.

Online web searches have played crucial roles in influencing consumers’ purchasing decisions. Web search traffic information enables researchers and practitioners to better understand consumers in terms of their preferences and interests, among other things. The purpose of this paper is to use web search traffic information provided by Google Trends to derive relationships among product brands as well as those between product brands and product attributes to propose a method to enhance the visibility of consumer brand positioning. This study builds upon the interesting observation that consumers’ behavior in performing simultaneous searches, or searches including two or more keywords, can be converted into data indicating relationships among brands as well as those between brands and their attributes. The study focuses on the cases of hybrid cars and tablet PCs, and applies a social network analysis method to identify these relationships. Time series information on web search traffic is used because it can track these two product groups from the early stages to the present. This step is completed to verify the changes in the status of each brand and in their relationships that occurred in consumers’ minds over time. Results show that consumers’ web search behaviors reveal the brand positioning and brand-attribute associations in their minds. Specifically, using consumers’ simultaneous search data, the authors derived relationships among brands (brand-brand network) from consumers’ behaviors of searching simultaneously for two brands and the relationships between brands and attributes (brand-product attributes network) from consumers’ behavior of searching simultaneously for a specific brand and certain product attributes. Theoretically, this study verifies that consumers’ web search traffic information can be used to microscopically identify the positions of individual brands and their relationships in the minds of consumers. Regarding practical applications, this study proposes a method that can be used by companies to track how consumers perceive their brands by performing a simple and cost-effective analysis using the free search traffic information provided by Google.