Research Article

Consumer Trust in E-Commerce: The Role of Personalisation, Security, and Brand Authenticity

Authors

  • Md Naim Mukabbir Independent Researcher

Abstract

Consumer trust has become a critical determinant of success in the rapidly expanding e-commerce landscape. As online marketplaces grow increasingly competitive, businesses must prioritise trust-building strategies to attract, engage, and retain customers. This study examines how three key factors—personalisation, security, and brand authenticity—shape consumer trust in digital commerce environments. Personalisation enhances user experience by delivering tailored recommendations, adaptive interfaces, and relevant product offerings, thereby strengthening emotional connection and perceived value. Security mechanisms, including data protection, secure payment systems, and transparent privacy policies, significantly influence consumers’ willingness to transact online and reduce perceived risk. Brand authenticity, grounded in transparency, consistent communication, and ethical business conduct, fosters credibility and long-term loyalty. Through a synthesis of current literature and emerging industry practices, this paper explores the interplay between these dimensions and their collective impact on consumer trust formation. The study argues that e-commerce platforms must integrate personalised experiences with robust security frameworks and genuine brand identity to cultivate strong and sustainable consumer trust. These insights offer valuable implications for digital marketers, platform designers, and policymakers seeking to strengthen trust and engagement within the online marketplace.

Article information

Journal

British Journal of Multidisciplinary Studies

Volume (Issue)

3 (2)

Pages

18-26

Published

2024-12-20

How to Cite

Md Naim Mukabbir. (2024). Consumer Trust in E-Commerce: The Role of Personalisation, Security, and Brand Authenticity. British Journal of Multidisciplinary Studies, 3(2), 18-26. https://doi.org/10.32996/bjmss.2024.3.2.3

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Keywords:

Predictive algorithms, algorithmic bias, digital surveillance, social inequality, automated governance