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Articles

‘The tweeting sponsor’: effect of a sponsor’s SNS message articulation/interactivity on consumers’ online response

, &
Pages 227-250 | Received 12 Dec 2019, Accepted 28 May 2020, Published online: 15 Jun 2020
 

ABSTRACT

Research Question: The study proposes that a sponsor’s social networking site (SNS) message has two components, articulation and interactivity, which are positively associated with a user’s sentiment (POS) and e-word-of-mouth (e-WOM). The relations are, further, moderated by the sponsor-event functional fit.

Research Method: The data were collected from Twitter and the proposed relations analysed using seemingly unrelated regression. The sample size was 131 sponsors for tennis grand slam events across the years 2016–17.

Findings: Significant effects of articulation on POS/e-WOM and of interactivity on e-WOM were found. The sponsor-event functional fit moderated the effect of event-focused articulation on POS/e-WOM and of interactivity on e-WOM.

Implications: Besides conceptualizing a sponsor’s two SNS message components, this study examines their effect on the consumers’ online response. The importance of SNS message articulation and interactivity, contingent to a sponsor’s functional fit with the event, for creating maximum impact is discussed.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

2 Cohen’s Kappa.

3 Fleiss’ Kappa.

4 Product/service/firm-focused articulation was considered as reference category, with dummy variable for no-articulation (ART_3) and event-focused articulation (ART_4) introduced; β (ART_4) = −0.05 (p > 0.05).

5 Same as for Model 1A; β (ART_4) = 0.44 (p > 0.05).

6 Moderate-fit was made the reference category and dummy variables for low-fit (Fit_Level3) and high-fit (Fit_Level4) were introduced; β (ART_2 x FIT_Level4) = −0.95 (p<0.05).

7 Moderate-fit was made the reference category and dummy variables for low-fit (Fit_Level3) and high-fit (Fit_Level4) introduced; β (ART_2 x FIT_Level4) = −1.10 (p<0.05); β (INT x FIT_Level4) = −0.25 (p<0.05).

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