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?
T2  - 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
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/60887
SN  - 1044-7318
SN  - 1532-7590
SP  - 1
EP  - 30
PB  - Taylor & Francis
CY  - New York
ER  -