The current study looks at the blogger influence phenomenon from a different theoretical perspective than existing literature did
2019
Key concepts
Scholarcy highlights
- Bloggers’ influence on consumers has been explored in the current literature as a crucial aspect of the post-modern era
- Most of the studies used data mining techniques and assessed on visible characteristics of the bloggers like the number of in-links, comments received, connection between users and/or social network indices. The outcome of these efforts are the development of aggregate metrics on how influential a blogger is
- This poses certain constraints in the modelling approach to blogger influence and the attendant metrics reviewed by Khan, et al as the occurrence of influence is not assessed
- The present study examines how the characteristics of the blogger and blog’s content interact with visitor’s involvement and blog visitors’ goals of visit
- The first step was to choose the optimal number of classes by specifying latent class analysis models with various numbers of classes
- We evaluated the number of classes in the LCA models by comparing several statistical criteria, including the Akaike information criterion, the Bayesian information criterion, the adjusted BIC, entropy, the Vuong-Lo-MendellRubin likelihood ratio test and the Lo-Mendell-Rubin adjusted likelihood ratio test
- The use of the number of followers as a key influence metric needs to be re-examined in view of the visitors’ goals and issue involvement
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