Examining the key determinants towards online pro-brand and anti-brand community citizenship behaviours
Purpose: The purpose of this paper is to propose a research model to identify the key determinants and examine their impact towards online pro-brand and anti-brand community citizenship behaviours (CCBs). Design/methodology/approach: A survey based on the research model is used to collect empirical data from 260 and 200 members of online pro-brand communities (OBCs) and online anti-brand communities (OABCs), respectively. A two-stage approach employing fuzzy-set qualitative comparative analysis and artificial neural network (ANN) is first applied to uncover new observations. Findings: Moral identity and positive brand emotion (BE) are the two most influential factors driving both online pro-brand and anti-brand CCBs. A higher level of internalisation might be required to exhibit online anti-brand CCB as opposed to online pro-brand CCB. This contradicts the current understanding that anti-brand behaviours are less morally restricted given the virtuality and anonymity of online communities. OABC members may need to better justify themselves internally to overcome positive BE when exercising anti-brand action. Also, brand identification, brand dis-identification and BE would be used to identify two types of OABC members. Research limitations/implications: The effect of motives other than pro-social remains unclear on online pro-brand and anti-brand CCBs. Originality/value: This is the first paper to develop two new dimensions which provide a more complete definition of CCB. Also, some new observations are uncovered by comparing the effect of different key determinants on online pro-brand CCB against that of online anti-brand CCB. The research model can be used to define and improve member (or brand) engagement which would enhance the management of OBCs and OABCs.
Year of publication: |
2018
|
---|---|
Authors: | Wong, T.C. ; Haddoud, Mohamed Yacine ; Kwok, Y.K. ; He, Hongwei |
Published in: |
Industrial Management & Data Systems. - Emerald, ISSN 0263-5577, ZDB-ID 2002327-3. - Vol. 118.2018, 4 (14.05.), p. 850-872
|
Publisher: |
Emerald |
Saved in:
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