Suchergebnisse

Korean migrations to and within China -- Ethnicity or nationality? : Korean identities in China -- South Korean and Korean Chinese business relations in China -- Korean business, intra-ethnic conflict, and adaptive strategies -- Relations between Korean Chinese and South Koreans in the service sector -- Community networks and activities

PurposeSocial media (e.g., e-WOM) and traditional media (e.g., media coverage) serve different roles in a firm's marketing activities and also interact with each other, which in turn affect the market outcome. In addition, how market outcome affects the two types of media in turn has not been examined, which brings the need for a holistic framework. The rare study that examines this relation mostly relies on the volume of media rather than the valence. This study examines the interdependent relation between the volume and valence of social media, the volume of traditional media and TV ratings.Design/methodology/approachForty-one South Korean TV drama shows from October 2014 to March 2016 were analyzed using the 3SLS estimation to examine the interdependent relation between the variables.FindingsFirst, the volume of traditional media has a negative effect on the volume of social media. Second, ratings negatively affect the valence of social media. Third, the volume of traditional media is found to have a negative effect on ratings. This is explained by the displacement effect.Originality/valueThis study is one of the very few studies that examine the interdependent relation between various earned media and market outcomes in one framework. In addition, it has originality in that it considers the valence of social media, which is an important dimension in analyzing earned media. Our results show negative effects of news media on TV ratings and e-WOM, which diverge from common intuition.

Purpose
The purpose of this paper is to investigate the relation between average ratings (viewership) and the volume and valence of electronic word of mouth (e-WOM) for early episodes of TV shows.


Design/methodology/approach
Linear regression was performed in which the dependent variable is average TV ratings and main independent variables are volume and valence of e-WOM. The study used a Breusch–Pagan test to detect heteroscedasticity. Accordingly, the model is analyzed using heteroscedasticity-consistent standard error estimators.


Findings
The results show that the volume of the early e-WOM does not significantly contribute to explaining average ratings, but the valence does.


Originality/value
Because the advertising revenue of television broadcasters is determined according to expected TV ratings, the average ratings should be predicted as early as possible. This study shows that analyzing early e-WOM helps predict average ratings.

PurposeThe purpose of this study is to examine how the usage of mobile devices influences text-posting behavior in the online review-generation process. This study attempts to improve the understanding of the negative impacts of mobile channels on the quality of online reviews.Design/methodology/approachThe authors develop a series of hypotheses to investigate the text-posting behaviors with mobile device usage. To examine the authors' hypotheses, the authors collect online reviews posted in London hotels on Booking.com. The authors first use a logistic regression model to examine the relationship between the usage of mobile devices and text-posting behavior. Then, the authors explored the characteristics of textual content in mobile reviews compared to reviews written via traditional devices.FindingsThe authors' finding shows that the use of mobile devices negatively influences text-posting behavior. Compared to traditional devices, consumers are less likely to post texts in their reviews with mobile devices. Although consumers decide to post text comments in consumers' reviews, the quality of textual content is relatively low – short in length, with limited analytical thinking and less authenticity.Originality/valueTo the best of the authors' knowledge, no study has attempted to explore text generation in review-posting behaviors in the context of mobile channels. Also, the authors' findings show the negative effects of using mobile channels on the value of generated information, which is counterintuitive to previous research.