Finding determinants of e-commerce success: a PLS-SEM approach

Abstract

Purpose With the growth in internet technology, the competition between the e-commerce firms has become fierce. This has forced these online vendors to consider customer-centric strategies apart from the retail strategies for generating revenue. The purpose of this paper is to propose a structural model to study the interrelationship between a formative endogenous latent variable (LV), i.e. e-commerce success, and other LVs representing the customer-oriented success factors such as website service quality (WSQ), customer support system (CSS), personalization and electronic word-of-mouth (EWOM). Design/methodology/approach The authors develop a structural model to validate the determinants of electronic commerce success. Survey-based data obtained from 265 respondents are used to validate the model hypotheses. To analyze the data, partial least squares-structural equation modeling (PLS-SEM) is performed using smartPLS 2.0 software. The results on the interrelationships between the constructs are determined using path analysis. Findings The data analysis results infer the impact of these success factors on e-commerce success systems. After applying bootstrapping technique, the authors observed that WSQ, CSS, personalization and EWOM have a significant positive effect on e-commerce system success (ESS). Further studies can be performed considering mobile commerce and their critical success factors. Practical implications The findings of the study emphasize on the importance of these four exogenous variables for e-businesses in order to achieve a competitive edge over their competitors. The study provides a detailed managerial implication with respect to each causal relationship, so as to suggest some remedial measures to gain customer market. Originality/value Here, the authors consider an empirical model which shows the determinants of ESS. To the best of the authors’ knowledge, a distinctive system success framework is modeled considering a unique combination of exogenous variables not considered by previous studies.