Customer engagement in social media: a framework and meta-analysis
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REVIEW PAPER
Customer engagement in social media: a framework and meta-analysis Fernando de Oliveira Santini 1 & Wagner Junior Ladeira 1 & Diego Costa Pinto 2 Claudio Hoffmann Sampaio 4 & Barry J. Babin 5
&
Márcia Maurer Herter 3 &
Received: 17 August 2018 / Accepted: 28 April 2020 # Academy of Marketing Science 2020
Abstract This research examines customer engagement in social media (CESM) using a meta-analytic model of 814 effect sizes across 97 studies involving 161,059 respondents. Findings reveal that customer engagement is driven by satisfaction, positive emotions, and trust, but not by commitment. Satisfaction is a stronger predictor of customer engagement in high (vs. low) convenience, B2B (vs. B2C), and Twitter (vs. Facebook and Blogs). Twitter appears twice as likely as other social media platforms to improve customer engagement via satisfaction and positive emotions. Customer engagement is also found to have substantial value for companies, directly impacting firm performance, behavioral intention, and word-of-mouth. Moreover, hedonic consumption yields nearly three times stronger customer engagement to firm performance effects vis-à-vis utilitarian consumption. However, contrary to conventional managerial wisdom, word-of-mouth does not improve firm performance nor does it mediate customer engagement effects on firm performance. Contributions to customer engagement theory, including an embellishment of the customer engagement mechanics definition, and practical implications for managers are discussed. Keywords Customer engagement . Firm performance . Meta-analysis . Online consumer behavior . Social media
Introduction Marketing practitioners and scholars recognize that customer engagement in social media is an important marketing outcome
(Hollebeek et al. 2014; Rietveld et al. 2020; Simon and Tossan 2018; Wang and Kim 2017). Nine out of ten medium and large businesses spend a minimum of 11% of their total marketing budget on social media platforms like Twitter, Instagram,
John Hulland and Mark Houston served as editors for this article. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11747-020-00731-5) contains supplementary material, which is available to authorized users. * Diego Costa Pinto [email protected] Fernando de Oliveira Santini [email protected] Wagner Junior Ladeira [email protected] Márcia Maurer Herter [email protected]
1
Universidade do Vale do Rio dos Sinos (UNISINOS), Av. Unisinos, São Leopoldo, RS 950, Brazil
2
NOVA Information Management School|, Universidade NOVA de Lisboa, Campus de Campolide, Lisbon, Portugal
3
Universidade Europeia, Quinta do Bom Nome, Estr. Correia, 53 Lisbon, Portugal
4
Pontifícia Universidade Católica do Rio Grande do Sul (PUC/RS), Av. Ipiranga, Porto Alegre, RS 6681, Brazil
5
University of Mississipi, P.O. Box 1848, University, MS 38677, USA
Claudio Hoffmann Sampaio [email protected] Barry J. Babin [email protected]
J. of the Acad. Mark. Sci.
Facebook, Pintere
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