Impact of Online Review on Consumers’ Online Purchasing Intention An Empirical Study on University Students in Bangladesh
Keywords:
Online review, Consumer behavior, Online purchasing intention, Online shoppingAbstract
Research purpose: This study examines how online reviews influence consumers’ online purchasing intention in Bangladesh, a rapidly growing e-commerce market where trust, product quality verification, and delivery delays remain salient barriers. Design/methodology/approach: Primary survey data were collected via a Google Forms questionnaire from Bangladeshi online shoppers. The relationships between online review
attributes—review credibility, review valence, review contemplation, and review endorsement—and purchasing intention were analyzed using ordinal logistic regression. Findings: All four review attributes exhibit statistically significant associations with consumers’ online purchasing intention. Collectively, the results indicate that online reviews play a decisive role in shaping purchase intentions within the Bangladeshi context. Originality/value: The study provides context-specific evidence from Bangladesh and differentiates the effects of distinct review attributes (credibility, valence, contemplation, endorsement), offering a nuanced understanding of how reviews translate into purchasing intention in an emerging ecommerce environment. Practical implications: E-commerce platforms and sellers should strengthen review systems by promoting credible, informative, and well-endorsed reviews; facilitating thoughtful review content; and implementing mechanisms that enhance trust (e.g., verified-purchase badges, anti-fraud checks). Such actions can mitigate perceived risks, build consumer confidence, and increase conversion rates.
Research limitations: The use of self-reported, cross-sectional survey data collected online may limit causal inference and generalizability beyond the sampled population. Future research could employ longitudinal designs, incorporate behavioral purchase data, and test moderating factors (e.g.,
product type, platform trust) to validate and extend these findings.
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