Abstract
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 (fsQCA) and artificial neural network (ANN) is firstly applied to uncover new observations.
Findings - Moral identity and positive brand emotion 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 brand emotion when exercising anti-brand action. Also, brand identification, brand dis-identification and brand emotion 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. Our research model can be used to define and improve member (or brand) engagement which would enhance the management of OBCs and OABCs.
| Language | English |
|---|---|
| Number of pages | 26 |
| Journal | Industrial Management and Data Systems |
| Early online date | 13 Apr 2018 |
| DOIs | |
| Publication status | E-pub ahead of print - 13 Apr 2018 |
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Keywords
- online community participation
- social support
- social identity theory
- community citizenship behaviour
- fuzzy-set qualitative comparative analysis
- artificial neural network
Cite this
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Examining the key determinants towards online pro-brand and anti-brand community citizenship behaviours : a two-stage approach. / Wong, Tse Chiu; Haddoud, Mohamed; Kwok, Y.K.; He, Hongwei.
In: Industrial Management and Data Systems, 13.04.2018.Research output: Contribution to journal › Article
TY - JOUR
T1 - Examining the key determinants towards online pro-brand and anti-brand community citizenship behaviours
T2 - Industrial Management and Data Systems
AU - Wong, Tse Chiu
AU - Haddoud, Mohamed
AU - Kwok, Y.K.
AU - He, Hongwei
PY - 2018/4/13
Y1 - 2018/4/13
N2 - Purpose - A research model is proposed 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 (fsQCA) and artificial neural network (ANN) is firstly applied to uncover new observations.Findings - Moral identity and positive brand emotion 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 brand emotion when exercising anti-brand action. Also, brand identification, brand dis-identification and brand emotion 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. Our research model can be used to define and improve member (or brand) engagement which would enhance the management of OBCs and OABCs.
AB - Purpose - A research model is proposed 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 (fsQCA) and artificial neural network (ANN) is firstly applied to uncover new observations.Findings - Moral identity and positive brand emotion 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 brand emotion when exercising anti-brand action. Also, brand identification, brand dis-identification and brand emotion 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. Our research model can be used to define and improve member (or brand) engagement which would enhance the management of OBCs and OABCs.
KW - online community participation
KW - social support
KW - social identity theory
KW - community citizenship behaviour
KW - fuzzy-set qualitative comparative analysis
KW - artificial neural network
UR - http://www.emeraldinsight.com/loi/imds
U2 - 10.1108/IMDS-07-2017-0313
DO - 10.1108/IMDS-07-2017-0313
M3 - Article
JO - Industrial Management and Data Systems
JF - Industrial Management and Data Systems
SN - 0263-5577
ER -