Predicting user behavior on s-commerce platforms: a novel model

Abstract

Purpose

This study investigates the influence of the wisdom of the crowd (WSC), trust and perceived value on consumer purchase intentions within social commerce (s-commerce) platforms. By constructing a novel theoretical model, the research aims to delineate the interrelationships among these variables, addressing an emerging area in social interactions and information technology.

Design/methodology/approach

To empirically test and validate the proposed model, the study collected data from 442 Facebook users familiar with online shopping. The analysis employed Structural Equation Modeling – Partial Least Squares (SEM-PLS) to test the hypotheses and examine the relationships between WSC, trust, perceived value and purchase intentions.

Findings

The findings confirm that WSC significantly influences trust, perceived value and the intention to purchase on s-commerce platforms. Both perceived value and trust are substantial determinants of purchase intentions. Notably, the PLS analysis revealed that WSC accounts for 36.8% of the variance in trust and 33.1% of the variance in perceived value related to purchasing decisions on s-commerce platforms.

Originality/value

This research contributes uniquely to the ongoing discourse on s-commerce adoption by integrating WSC as a pivotal factor in understanding perceived value and consumer adoption intentions. It provides a fresh perspective on how collective intelligence affects consumer behavior in digital marketplaces, enriching the theoretical and practical understanding of s-commerce dynamics.

Citation

Al-Omoush, K.S. and Shuhaiber, A. (2024), "Predicting user behavior on s-commerce platforms: a novel model", Kybernetes, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/K-04-2024-1040