Purpose The purpose of this paper is to examine the driving factors of user innovation behaviors using the case of smartphone applications to estimate the indirect and direct effects of consumers’ attitudes toward user-generated content (UGC). Design/methodology/approach This study proposes a structural model to examine the relationship between user innovation behaviors toward UGC and three attitude factors: involvement, consumer knowledge and customer orientation. The empirical analysis is based on a consumer survey that examines the commonalities and differences between Japan and China. In each country, two social media services are chosen as representative cases of the UGC business model to measure user innovation behaviors toward the quality and quantity aspects. Findings Customer orientation is the most significant driving factor of user innovation behaviors toward UGC. It positively affects both the number of followers and the frequency of information transmissions. In particular, for the quality dimension of user innovation, customer orientation has a more significant effect on the number of followers than does familiarity. Originality/value This study emphasizes the quality aspect of user innovation. Previous research has focused on the quantity of user innovation behaviors by measuring the amount of information. However, this research measures both the quality and the quantity aspects with the number of followers and the frequency of uploading content. The findings of this study suggest that companies should maintain relationships with highly customer-oriented users to manage content quality.

Purpose This study aims to enhance knowledge on marketing strategies to increase repeat visitors. Furthermore, the authors suggest using appropriate destination information tailored to first-time visitors and repeat visitors as social capital. Design/methodology/approach This study compares the differences in satisfaction between first-time foreign tourists and those repeat visiting. The authors apply a theoretical framework based on optimal distinctiveness theory (ODT) and consumer knowledge to determine which actions maximize the satisfaction of each group. Then, the relationships among assimilation desire, differentiation desire and satisfaction are quantitatively analyzed. Findings The results show the difference in the relationship between assimilation and travel satisfaction for first-time visitors and repeat visitors. First-time visitors are satisfied with popular sightseeing spots with higher assimilation level, whereas repeat visitors are satisfied with moderately unpopular sightseeing spots with lower assimilation level. The results clarify that information reflecting only the popularity of destinations is significantly effective for first-time visitors, but unsuitable for repeat visitors. Therefore, it would be possible to propose to repeat visitors a combination of “moderately differentiated” destinations. Originality/value The first contribution is that on the basis of Brewer (1991), the quantitative analysis confirmed that the social identity of an individual changes from assimilation to differentiation with the accumulation of experience until the optimal point is found. The second contribution is that we combined several fields such as ODT (Brewer, 1991), familiarity (Alba and Hutchinson, 1987), trial/repeat behavior (Iyengar et al., 2015) and reference groups (Peter & Olson, 2010). The third contribution is that the authors proposed marketing strategies on the basis of the empirical analysis to increase the number of inbound tourists.

This study examines the factors involved in the spread of digital transformation (DX) in Japan, which had previously been lagging in digitalization, during the COVID-19 pandemic, which began in 2020. To accomplish this, we analyzed 8,297 news articles that mentioned either "digital transformation" or "digitalization" during the three-year period from 2019 to 2021. We found that the public sector first began instituting DX policies soon after the pandemic broke out and was then followed by the private sector, meaning that the public and private sectors became actively involved in DX during the pandemic.