Application of social media analytics in tourism crisis communication

Given the newly established communication environment of social media and highly unpredictable crisis situations, this study questioned how tourists facing an unexpected crisis situation use social media to communicate and search for information. To this end, this study developed a multi-phased social media analytic framework (data crawling, data processing and text mining, social network analysis, semantic network analysis, and network visualization) to assess the structure of information exchanges between the members of a tourism organization’s social network community and identified influential actors and information content within the social network. This study’s findings suggest genuine ways of relating with and utilizing opinion leaders and influencers in social media marketing communication as well as crisis communication. The authors expect this proposed methodological framework of social media analytics to help other scholars scientifically identify and implement the proper methodologies for utilizing social media data.     

The price of going green: the role of greenness in green bond markets

In this paper, we empirically investigate how greenness information is priced in the green bond market. Our comparison of liquidity-adjusted yield premiums of green bonds versus synthetic conventional bonds indicates that, on average, there is no robust and significant yield premium or discount on green bonds. However, green bonds certified by an external reviewer enjoy a discount of about 6 bps. Furthermore, green bonds that obtain a Climate Bonds Initiative certificate show a discount of around 15 bps. The findings suggest that a universally accepted greenness measure can benefit the development of the green bond market.     

YouTubers’ networking activities during the 2016 South Korea earthquake

While YouTube has become an important social networking platform for risk and crisis communications, research into its role and use during environmental disasters has not been conducted. The present study investigates how Korean YouTubers reacted during the 2016 Gyeongju earthquakes. Two kinds of data were collected from the most popular YouTube clips on the earthquake (from AfreecaTV and YonHap news): the most frequently used words in the replies to the comments and the networked forums among YouTubers. Findings suggest that YouTube has become a channel for quickly increasing public awareness of crises and for promoting safety strategies. InDegree Centralization is higher in professional videos. Hierarchy measure’s value is one, which means the reply-to network is not two-way. There is sparse close-knittedness in amateur videos. Community clusters emerge in amateur videos over time. The results also reveal that YouTubers on AfreecaTV are more likely to express emotional opinions than their counterparts on YonHap news are.     

Pay dispersion among the top management team and outside directors: Its impact on firm risk and firm performance

Two key groups central to improving firm performance are the top management team (TMT) and the board of directors. Executives undertake strategic actions, whereas board members fulfill their resource provision and monitoring roles. Drawing on tournament theory and equity theory, we propose that high pay dispersion among outside directors and the TMT is positively associated with strategic risk, whereas high (low) TMT pay dispersion and low (high) outside director pay dispersion are positively associated with firm performance. Our predictor is the unexplained component of horizontal pay dispersion, or the residual of pay dispersion resulting from regressing pay on observable firm, industry, period, and individual characteristics. Our results highlight the importance of unexplained pay dispersion for TMTs, but not for boards of directors, in improving firm performance.     

Varying Coefficient Regression Models: A Review and New Developments

Varying coefficient regression models are known to be very useful tools for analysing the relation between a response and a group of covariates. Their structure and interpretability are similar to those for the traditional linear regression model, but they are more flexible because of the infinite dimensionality of the corresponding parameter spaces. The aims of this paper are to give an overview on the existing methodological and theoretical developments for varying coefficient models and to discuss their extensions with some new developments. The new developments enable us to use different amount of smoothing for estimating different component functions in the models. They are for a flexible form of varying coefficient models that requires smoothing across different covariates' spaces and are based on the smooth backfitting technique that is admitted as a powerful technique for fitting structural regression models and is also known to free us from the curse of dimensionality.     

Does local political support influence financial markets? A study on the impact of job approval ratings of political representatives on local stock returns

Using data on job approval ratings of governors, U.S. senators, and the president, we find that firms located in states with high approval ratings outperform firms located in states with low approval ratings by .64% per month. Furthermore, this relationship is stronger when investors are actively involved in politics, when local politicians are closer to the center of political power, for small firms that have a larger proportion of local investors, and for financially strong areas where investors are ready to execute investments in local stocks. Overall, our study shows that investors’ political sentiment is important in determining stock returns.     

South Korea’s outward direct investment and its dyadic determinants: Foreign aid,bilateral treaty and economic diplomacy

This study investigates the factors that affect South Korean outward foreign direct investment (FDI) in developing countries. Most previous studies focus on monadic factors and do not consider how and to what extent bilateral relationships between South Korea and the host countries affect the investment decisions of Korean firms. The current study finds that interstate factors such as South Korea's international investment treaties with and official development assistance to host countries have positive effects on FDI to these countries, while presidential visits have strong and statistically significant effects on FDI only in countries located in non-Asian regions, especially the African continent. The findings suggest that the effects of bilateral relations on South Korea's FDI vary depending on the geographic location of the host country.     

Industry Shock Expectations,Interindustry Linkages,and Merger Waves: Evidence from the Hospital Industry

It is well known that mergers often occur in waves, and this paper develops a new mechanism for merger waves: expectations over industry shocks. We develop a simple test of this explanation and use it to explore the role of expectations in the context of the 1990s hospital merger wave. Managed care such as Health Maintenance Organizations (HMOs) started to become popular in the late 1980s and ultimately became an important player in the health insurance market. Our empirical analysis shows that the expected increase in the popularity of HMOs was partly responsible for the hospital merger wave of the 1990s: hospitals feared that the “innovation” of managed care in the downstream insurance market would penetrate the upstream hospital market and responded to this belief by merging. Our results show the importance of incorporating expectations and interindustry linkages into the understanding of merger waves.     

Short-term forecasting of Japanese tourist inflow to South Korea using Google trends data

We utilize the Internet search data from Google Trends to provide short-term forecasts for the inflow of Japanese tourists to South Korea. We construct the Google variable in a systematic way by combining keywords to minimize mean squared or mean absolute forecasting errors. We augment the Google variable to the standard time-series forecasting models and compare their forecasting accuracies. We find that Google-augmented models perform much better than the standard time-series models in terms of short-term forecasting accuracy. In particular, Google models show better out-of-sample forecasting performance than in-sample forecasting.     

Residents’ attitudes toward future tourism development in terms of community well-being and attachment

This study explores residents’ attitudes toward future tourism development based on their community well-being (CWB) and community attachment. Focusing on the case of Gamcheon Culture Village in Busan, South Korea, which was developed during an urban regeneration project in 2009, an exploratory factor analysis was conducted. The main findings of this study are: (1) CWB is supported by five variables including income effects, social participation, safety service, infrastructure service, and environmental effect; (2) not only does CWB influence community attachment but attachment also effects residents’ attitudes; and (3) the most effective variable of CWB is income effect, and safety service for community attachment. These results can help to provide effective strategies to encourage residents to have positive attitudes about further tourism development in a community-based tourism destination.