The Role of Emotional Marketing and eWOM in Sustaining Competitive Advantage in the Digital Era: A Dynamic Capabilities-Based Strategic Framework

Keywords: Emotional marketing, electronic word of mouth, dynamic capabilities, digital era, sustainable competitive advantage.

Abstract

Emotional marketing has become a paradigm shift for businesses' survival and success in today's competitive environment, as it enables them to build customer loyalty and increase sales. In today's digital age, electronic word of mouth (eWOM) is a potent tool that customers can use to communicate their emotions to a large audience. Thus, managing customer emotions can pay off handsomely for businesses, as eWOM can rapidly spread positive emotions to a large audience. However, the business environment of the twenty-first century is uncertain and complex, necessitating the development of dynamic capabilities to respond to impending change. This research combines three contemporary streams of thought, namely emotional marketing (as sensing capability), eWOM (as seizure capability), and dynamic capabilities (as to respond capability). As a result, the study develops a dynamic capabilities-based strategic framework that demonstrates the critical role of emotional marketing and eWOM in a firm's capability to sustain its competitive advantage in the digital era. Furthermore, the research suggests that the proposed EM-WOM-DC strategic framework for sustainable competitive advantage strengthens the relationship between emotional marketing and sustainable competitiveness and the relationship between eWOM and sustainable competitiveness.

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Author Biography

Ibrahim Abdullah Alhamad, University of Ha'il, Kingdom of Saudi Arabia.

Department of Management and Information Systems, College of Business Administration, University of Ha'il, Kingdom of Saudi Arabia.

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Published
2022-04-20
How to Cite
Alhamad, I. A. (2022). The Role of Emotional Marketing and eWOM in Sustaining Competitive Advantage in the Digital Era: A Dynamic Capabilities-Based Strategic Framework. Amazonia Investiga, 11(51), 281-290. https://doi.org/10.34069/AI/2022.51.03.28
Section
Articles
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