TY  - JOUR
A1  - Alnoor, Alhamzah
A1  - Tiberius, Victor
A1  - Atiyah, Abbas Gatea
A1  - Khaw, Khai Wah
A1  - Yin, Teh Sin
A1  - Chew, XinYing
A1  - Abbas, Sammar
T1  - How positive and negative electronic word of mouth (eWOM) affects customers’ intention to use social commerce?
BT  - a dual-stage multi group-SEM and ANN analysis
JF  - International journal of human computer interaction
N2  - Advances in Web 2.0 technologies have led to the widespread assimilation of electronic commerce platforms as an innovative shopping method and an alternative to traditional shopping. However, due to pro-technology bias, scholars focus more on adopting technology, and slightly less attention has been given to the impact of electronic word of mouth (eWOM) on customers’ intention to use social commerce. This study addresses the gap by examining the intention through exploring the effect of eWOM on males’ and females’ intentions and identifying the mediation of perceived crowding. To this end, we adopted a dual-stage multi-group structural equation modeling and artificial neural network (SEM-ANN) approach. We successfully extended the eWOM concept by integrating negative and positive factors and perceived crowding. The results reveal the causal and non-compensatory relationships between the constructs. The variables supported by the SEM analysis are adopted as the ANN model’s input neurons. According to the natural significance obtained from the ANN approach, males’ intentions to accept social commerce are related mainly to helping the company, followed by core functionalities. In contrast, females are highly influenced by technical aspects and mishandling. The ANN model predicts customers’ intentions to use social commerce with an accuracy of 97%. We discuss the theoretical and practical implications of increasing customers’ intention toward social commerce channels among consumers based on our findings.
Y1  - 2022
U6  - https://doi.org/10.1080/10447318.2022.2125610
SN  - 1044-7318
SN  - 1532-7590
SP  - 1
EP  - 30
PB  - Taylor & Francis
CY  - New York
ER  - 
TY  - JOUR
A1  - XinYing, Chew
A1  - Tiberius, Victor
A1  - Alnoor, Alhamzah
A1  - Camilleri, Mark
A1  - Khaw, Khai Wah
T1  - The dark side of metaverse: a multi-perspective of deviant behaviors from PLS-SEM and fsQCA findings
JF  - International journal of human–computer interaction
N2  - The metaverse has created a huge buzz of interest because such a phenomenon is emerging. The behavioral aspect of the metaverse includes user engagement and deviant behaviors in the metaverse. Such technology has brought various dangers to individuals and society. There are growing cases reported of sexual abuse, racism, harassment, hate speech, and bullying because of online disinhibition make us feel more relaxed. This study responded to the literature call by investigating the effect of technical and social features through mediating roles of security and privacy on deviant behaviors in the metaverse. The data collected from virtual network users reached 1121 respondents. Partial Least Squares based structural equation modeling (PLS-SEM) and fuzzy set Qualitative Comparative Analysis (fsQCA) were used. PLS-SEM results revealed that social features such as user-to-user interaction, homophily, social ties, and social identity, and technical design such as immersive experience and invisibility significantly affect users’ deviant behavior in the metaverse. The fsQCA results provided insights into the multiple causal solutions and configurations. This study is exceptional because it provided decisive results by understanding the deviant behavior of users based on the symmetrical and asymmetrical approach to virtual networks.
KW  - deviant behaviors
KW  - metaverse
KW  - sociotechnical
KW  - perspective
KW  - privacy
KW  - fsQCA
Y1  - 2024
U6  - https://doi.org/10.1080/10447318.2024.2331875
SN  - 1044-7318
SN  - 1532-7590
PB  - Taylor & Francis
CY  - London
ER  -