Negative MWOM and value co-destruction during destination crises

Purpose The purpose of this paper is to examine the impact of microblogging word of mouth (MWOM) through twitter on value co-destruction for Athens, as a tourism destination facing a sustained crisis. The study demonstrates the sentiment and sharing evolution of tweets, illustrating the value co-destruction of a tourism destination. Overall, the study expands understanding on the online footprints of MWOM in the field of tourism. Design/methodology/approach It uses social media focused data mining and sentiment analysis, to analyze more than 90,000 tweets posted by top twitter influencers between 2013 and 2015. The methodology that the authors have adopted follows seven steps: first, identification of the top-5 twitter influencers who use the hashtag #Athens, based on their klout score; second, collection of tweets from the top-5 twitter influencers, for the period from January 2013 until June 2015; third, collection of the retweets metadata of the above tweets and of the corresponding retweeter accounts (i.e. user id, name, screen name), together with the frequency of retweeting per tweet; fourth, collection of user metadata (i.e. location and number of followers) from the retweeter accounts; fifth, influence computation of retweetwers using their klout score; sixth, tweets classification based on the klout score of their retweeters; and seventh, sentiment analysis of the collected tweets. Findings The findings show the high potential of value co-destruction in virtual environments, through negative MWOM related to tourism destinations in crisis, and shared among highly influencing users, that disseminate negative stories through microblogging. The findings also reveal the existence of negativity bias that can reduce the risks of visiting a new destination facing a crisis and, at the same time, significantly destroy the destination’s value. Originality/value This is the first study to examine the impact of MWOM through twitter on a tourism destination facing a sustained crisis, such as Athens. This study uses social media focused data mining and sentiment analysis, to analyze more than 90,000 tweets posted by top twitter influencers between 2013 and 2015. The findings reveal the existence of negativity bias that can reduce the risks of visiting a new destination facing a crisis and, at the same time, significantly destroy the destination’s value.