Journal of Emerging Markets and Management

Revisiting the Effectiveness of Electronic Word-of-Mouth and DynamicCapability of E-Commerce

DOI:

https://doi.org/10.63385/jemm.v1i2.191

Keywords:

Customer Loyalty, Dynamic Capability, Electronic Word-of-Mouth, Fuzzy Set, Perceived Risk

Abstract

This study contributes to identifying relationships among electronic word-of-mouth (eWOM), dynamic capability, perceived risk, and customer loyalty in cross-border e-commerce. Purposive sampling was employed to obtain empirical data. We chose consumers with experience using cross-border e-commerce platforms as our subjects and collected data through an online questionnaire. Data were collected through consumer surveys, and analyses were conducted using descriptive statistics, factor analysis, reliability analysis, structural equation modeling (SEM), and fuzzy-set qualitative comparative analysis (fsQCA). SEM results support three research hypotheses, showing that enhancing eWOM increases customer loyalty, while improving dynamic capability reduces perceived risk and further strengthens loyalty. fsQCA results identify four distinct combinations of conditions sufficient to achieve high customer loyalty. Path A1 shows that consumers can maintain high customer loyalty if they have a high opinion of eWOM, even if they rate the dynamic capability of cross-border e-commerce low. Path A2 reveals that consumers will demonstrate high customer loyalty as long as they hold a high opinion of the dynamic capability of cross-border e-commerce, even if they have a low evaluation of eWOM, regardless of the perceived risk level. Path A3 indicates that customers will display high loyalty when they highly value eWOM, even in situations of high perceived risk. Path A4 shows that customers will maintain high loyalty when they perceive the dynamic capability of cross-border e-commerce to be strong, even if there is a high level of perceived risk. These findings provide both theoretical insights and practical guidance for e-commerce managers aiming to optimize customer loyalty strategies.

References

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    Copyright (c) 2025 Cheng-Feng Cheng, Hsi-Ching Chan, Shan-Ni Lee, Jui-Lin Cheng

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