Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/10455
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dc.contributor.authorDr. KE Xiaobo, Boben_US
dc.contributor.authorChen, Yangsenen_US
dc.contributor.authorDu, Helen S.en_US
dc.date.accessioned2024-09-07T02:14:08Z-
dc.date.available2024-09-07T02:14:08Z-
dc.date.issued2016-
dc.identifier.citationKe, X., Chen, Y., & Du, H. S. (2016). Achieving mobile social media popularity: An empirical investigation. In Liang, T. P., Hung, S. Y., Chau, P. Y. K., & Chang, S. I. (Eds.). PACIS 2016 Proceedings. PACIS 2016, Chiayi, Taiwan. Association for Information Systems.en_US
dc.identifier.isbn9789860491029-
dc.identifier.urihttp://hdl.handle.net/20.500.11861/10455-
dc.description.abstractThe emergence of mobile social media provides a great opportunity for firms to attain competitiveness along the way. Current research regarding the influence of firm-based mobile social media has just started, but the findings still cannot meet the needs for e-business to standout in the increasingly fierce competition. Hence, our study draws on the heuristic-systematic model and social influence theories to establish mobile social media popularity model. We posit that the heuristic cognitive cues (i.e., source credibility and content freshness) as well as the systematic cognitive cue (i.e., mobile trading navigability) can potentially affect the mobile social media popularity of a firm. We further posit that social influence takes the moderate role in the model. The content analysis result from 183 public WeChat platforms of the P2P lending companies has offered the empirical evidence to our hypotheses. This study expands our understanding of the related constructs from a social cognition perspective, and calls for design attention to influential media-embedded traits when developing mobile social media sites.en_US
dc.language.isoenen_US
dc.publisherAssociation for Information Systemsen_US
dc.titleAchieving mobile social media popularity: An empirical investigationen_US
dc.typeConference Paperen_US
dc.relation.conferencePacific Asia Conference on Information Systems, PACIS 2016en_US
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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