Asif Iqbal

This study analyses the comparative effects between E-WOM on online shopping platforms and social networking platforms on consumers’ purchase intention of smartphones in India. The E-WOM effect on buying intention has become an important context for many researchers due to its increasing importance in today’s world of digitalization. This study aims to assess the influence of E-WOM factors on these two platforms, including E-WOM credibility, E-WOM attitude, E-WOM quantity, and E-WOM format, on purchase decisions of smartphones. The data were collected using a questionnaire from 361 respondents in Uttar Pradesh, India. Multiple regression has been applied to empirically measure the influence of independent factors (E-WOM credibility, E-WOM attitude, E-WOM quantity, and E-WOM format) on the dependent factor (consumers’ purchase intention). The result indicates that E-WOM credibility, E-WOM quantity, and E-WOM format on online shopping platforms have more impact than E-WOM on social media on the purchase intention of smartphones. This study aids online companies in understanding the purchase patterns of consumers, and E-WOM on online shopping platforms is more effective in terms of credibility, quantity, and format as compared to E-WOM on social networking platforms toward buying intention of smartphones.

This study analyzed by comparing the effect of e-WOM (electronic word-of-mouth) virtual shopping websites and e-WOM from respondents on social networks on users’ smartphone buying intentions. A research frame is established based on four e-WOM components: e-WOM source credibility, e-WOM source quality, e-WOM source attitude, and e-WOM source format toward the purchase intention of a smartphone. The effect of the independent variables was empirically tested using multiple regression analysis on the dependent variable of customer buying intention. The research was conducted in Uttar Pradesh, a province in India, with 362 respondents administering a questionnaire. Descriptive statistics, ANOVA (analysis of variance), and regression analysis were applied to interpret the source data. The results of regression factors had a strong statistical influence with a probability value of .000 and R2 of .358 according to the outcomes, suggesting that the framework described 35.8 proportion of the variance and that all the factors were major antecedents of buying intention. This study assists digital businesses in determining consumer buying trends through e-WOM on digital platforms. This study proposes a novel concept to understand how e-WOM affects customers’ buying intent from social networks and e-commerce portals.

Acknowledgment
This study is supported via funding from Prince Sattam bin Abdulaziz University project number PSAU/2024/R/1445.