Chatbot-based services in online travel agency (OTA) are rapidly spreading in order to respond more agilely to consumers' needs based on the digitalization of the travel industry. Although AI chatbots use anthropomorphism to provide social experiences on behalf of humans, research results on its effects are mixed. Therefore, based on construal level theory, this study suggests the degree of anthropomorphism (low vs. high) of chatbots prime mental representations of different construal levels (low vs. high) and the fit between anthropomorphism and communication context (communication types and conversation types) has a positive effect on use behavior. This research method consisted of sentimental analysis for exploring use behavior of AI chatbots and two experimental studies (study 1 and study 2) to examine the hypotheses. The results of this study expand construal level theory and avatar research to provide an understanding of the anthropomorphism of AI chatbots.

Even though Mod is a cutting-edge business model that benefits a variety of multi-sided market participants, empirical research on Mod, the value co-creation activity of game users and game developers, is hard to come by. This study intends to look into how the combination of the Mod and the IP from the prior game affects user engagement. An experiment was carried out with Korean university students to examine the hypotheses. User engagement was found to increase with the use of the Mod and the IP from the previous games. On the other side, it was discovered that the impact of mod games on user engagement did not differ significantly from non-mod games when the previous game's IP was absent. The study's findings help establish the framework for afterwards empirical research by showing the effect of mod on user engagement.

Climate change effects are particularly apparent in many cool-season grasslands in South Korea. Moreover, the probability of climate extremes has intensified and is expected to increase further. In this study, we performed climate change vulnerability assessments in cool-season grasslands based on the analytic hierarchy process method to contribute toward effective decision-making to help reduce grassland damage caused by climate change and extreme weather conditions. In the analytic hierarchy process analysis, vulnerability was found to be influenced in the order of climate exposure (0.575), adaptive capacity (0.283), and sensitivity (0.141). The climate exposure rating value was low in Jeju-do Province and high in Daegu (0.36–0.39) and Incheon (0.33–0.5). The adaptive capacity index showed that grassland compatibility (0.616) is more important than other indicators. The adaptation index of Jeollanam-do Province was higher than that of other regions and relatively low in Gangwon-do Province. In terms of sensitivity, grassland area and unused grassland area were found to affect sensitivity the most with index values of 0.487 and 0.513, respectively. The grassland area rating value was low in Jeju-do and Gangwon-do Province, which had large grassland areas. In terms of vulnerability, that of Jeju-do Province was lower and of Gyeongsangbuk-do Province higher than of other regions. These results suggest that integrating the three aspects of vulnerability (climate exposure, sensitivity, and adaptive capacity) may offer comprehensive and spatially explicit adaptation plans to reduce the impacts of climate change on the cool-season grasslands of South Korea.