Abstract (150 Words)
Abstract
In the formation of tourism destination image (TDI), understanding and being able to measure, analyze, compare, and contrast the images projected by user-generated content(UGC) and destination marketing organizations(DMOs) is crucial in tourism management and destination marketing. This study aims to propose a specific way to measure and compare UGC and DMO projected images within 249 short videos. Using machine learning algorithms, four indicators (the number of short videos, the number of likes, comments and shares) were identified to measure the influences of DMO and UGC short videos, and extracted 7 dimensions representing the destination image extracted through video content analysis, namely, nature environment, infrastructure, culture and art, people, food and beverage, specific activities, and transportation. The data analysis further revealed statistical differences in several dimensions of these images at different destination’s life cycle. Theoretical and practical implications were also discussed.
Keywords
tourism destination image, destination’s life cycle, short video, video captaining,brand hijack
Who Dominate TDI? A Big Data Evidence from DMO and UGC Short Videos
Abstract
In the formation of tourism destination image (TDI), understanding and being able to measure, analyze, compare, and contrast the images projected by user-generated content(UGC) and destination marketing organizations(DMOs) is crucial in tourism management and destination marketing. This study aims to propose a specific way to measure and compare UGC and DMO projected images within 249 short videos. Using machine learning algorithms, four indicators (the number of short videos, the number of likes, comments and shares) were identified to measure the influences of DMO and UGC short videos, and extracted 7 dimensions representing the destination image extracted through video content analysis, namely, nature environment, infrastructure, culture and art, people, food and beverage, specific activities, and transportation. The data analysis further revealed statistical differences in several dimensions of these images at different destination’s life cycle. Theoretical and practical implications were also discussed.
Keywords
tourism destination image, destination’s life cycle, short video, video captaining,brand hijack