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Social media-driven customer engagement and movie performance: Theory and empirical evidence

Authors :
Javier Llorens
Xin (Robert) Luo
Ana Castillo
Jose Benitez
Source :
Decision Support Systems. 145:113516
Publication Year :
2021
Publisher :
Elsevier BV, 2021.

Abstract

Can social media-driven customer engagement help movie producers to increase movie sales? Movie producers use social media to boost customer engagement; however, our understanding of whether there is a relationship between pre-consumption customer engagement and movie sales is limited. This research explores what drives the success of movies on the opening-weekend. We examine the relationship between pre-consumption customer engagement driven by social media (i.e., personal and interactive engagement) and movie performance (i.e., opening-weekend box office revenues). Driven by the debate about the potential capacity of social media-driven customer engagement to improve movie performance and the limited understanding of the association of pre-consumption customer engagement and movie performance, this research suggests that social media-enabled customer engagement (i.e., personal and interactive engagement) has the potential to improve movie performance, and these two types of engagement can interact to make this effect stronger. We analyze these relationships drawing from the uses and gratifications theory and the social media affordances perspective that motivate customers to interact in social media. The theoretical model evaluation was tested on a unique and original dataset composed of 966 movies released in the U.K. and Spain. The empirical analysis suggests that personal and interactive engagement are positively related to movie performance, and the positive effects of personal and interactive engagement on movie performance are mutually reinforcing. This research contributes to Information Systems (IS) research by theorizing and empirically showing how customer engagement driven by social media creates business value by improving movie performance.

Details

ISSN :
01679236
Volume :
145
Database :
OpenAIRE
Journal :
Decision Support Systems
Accession number :
edsair.doi.dedup.....a8147b388ec4edf435825da21e18849d
Full Text :
https://doi.org/10.1016/j.dss.2021.113516