Unlocking value through an extended social media analytics framework: Insights for new product adoption

Abstract

Purpose

To unlock social media’s value, this study aims to integrate insights from several theoretical perspectives and the relevant literature, developing an extended social media analytics framework. It identifies the stages underlying the social media analytics process and tests the framework in three important and interconnected areas: social media (Twitter), new product adoption (iWatch and Google Glass) and social media analytic techniques (text mining and sentiment analysis).

Design/methodology/approach

Based upon a systematic review of different research approaches, theories and media types, this paper presents and tests an extended framework in three important and interconnected areas mentioned above.

Findings

This paper offers a theory-driven social media analytics framework. It validates the framework by providing concrete processes, examples, evidence and insights related to three chosen areas mentioned above, thereby helping managers create effective and efficient social media and new product development strategies.

Originality/value

This paper integrates insights from theories of the middle range (Merton, 1949), Campbell’s (1965) model of sociocultural evolution and Fan and Gordon’s (2014) social media analytics framework, developing its own extended social media analytics framework and validating it in three important and interconnected areas mentioned above. This paper demonstrates not only how the proposed framework can be applied to the context of new product development, but also how social media are transforming research approaches (qualitative, quantitative and mixed method) and the very nature of business itself (increased importance of digital business).

Citation

Wu, G.J., Xu, Z.“., Tajdini, S., Zhang, J. and Song, L. (2019), "Unlocking value through an extended social media analytics framework: Insights for new product adoption", Qualitative Market Research, Vol. 22 No. 2, pp. 161-179. https://doi.org/10.1108/QMR-01-2017-0044