Revisiting the antecedent of electronic word-of-mouth (eWOM) during COVID-19 Pandemic

Rani, Anshu; Shivaprasad, H. N.

doi:10.1007/s40622-021-00298-2

Cited by 9 publications

(4 citation statements)

References 50 publications

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“…Electronic word-of-mouth (e-WOM) refers to the impact of online reviews and personal recommendations on consumer behavior within the context of e-commerce [ 12 ]. According to the extended Technology Acceptance Model (TAM), e-WOM can significantly affect consumers' perception of an e-commerce platform's usefulness and trustworthiness [ 13 ].…”

Section: Theoretical Framework Literature Review and Hypothesis Devel...mentioning

confidence: 99%

Purchasing in the digital age: A meta-analytical perspective on trust, risk, security, and e-WOM in e-commerce

Handoyo

2024

Heliyon

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Section: Theoretical Framework Literature Review and Hypothesis Devel...mentioning

confidence: 99%

Purchasing in the digital age: A meta-analytical perspective on trust, risk, security, and e-WOM in e-commerce

Handoyo

2024

Heliyon

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“…Electronic wordof-mouth (e-WOM) in virtual groups has become a powerful tool for shaping positive brand images [32]. Social interactions in e-WOM are driven by motives like social connections, economic incentives, altruism, and self-esteem [33]. Weblog users are seen as highly credible, especially in institutionally related domains [24].…”

Section: • Customer Online Reviewsmentioning

confidence: 99%

Measuring Online Customer Satisfaction Based on Customer Reviews: Topic Modeling Method Using Latent Dirichlet Allocation (LDA) Algorithm

S Dhameeth

2024

J Market & Supply Chain Managem

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Companies invest significant resources in retaining their customers. Nonetheless, organizations have witnessed customer attrition due to inadequate loyalty. This trend is particularly prevalent among online customer bases. The root cause of this issue lies in the absence of an effective tool for measuring online customer satisfaction that surpasses the capabilities of existing methods. To address this concern, a quantitative study explored the dimensions of online customer satisfaction measurement and established a model applicable across industries for gauging and predicting online customer satisfaction. This was accomplished by conducting an online survey via SurveyMonkey with 384 respondents, employing supervised and unsupervised machine learning techniques in conjunction with the topic modeling algorithm, Latent Dirichlet Allocation (LDA). The findings of this study revealed a significant relationship between predictor variables such as navigation, playfulness, information quality, trust, personalization, and responsiveness and the target variable, online customer satisfaction, employing multiple linear modeling (LSM). Furthermore, it was observed that this phenomenon transcends age groups, impacting both younger and older customers alike. However, it is essential to acknowledge certain limitations, including the risk of overfitting, challenges in establishing external validity, a narrow focus on the retail sector (B2C), and a restricted scope limited to the United States market.

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“…Liu & Yan, 2022;Z. Liu et al, 2022;Rani & Shivaprasad, 2021). Businesses can use their e-WOM strategy to make information about their products and services readily available to consumers.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Marketing Communication Strategies Through Celebgrams on Perceptions of the Product among Indonesian Millennials

Zein,

Wagiati

2023

J. Komun.

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The rapid growth of social media has opened up vast opportunities for companies to capture the attention of potential customers. In this context, it has become imperative for brands to adapt their strategies to effectively target millennials through social media platforms. Notably, brands in the fashion industry have increasingly relied on online "celebrities" or influencers of social media (ISMs), commonly referred to as celebgrams on Instagram, to disseminate information and enhance consumer awareness of their products. This article aims to investigate the impact of celebgram endorsements on consumer perceptions of products by examining social comparatives and personal conformity. Experimental research was conducted with three conditions: celebgram, brand, and surveillance. Through a comprehensive questionnaire consisting of forty-eight questions related to celebgram, personal conformity, social comparative, and product perceptions, data was collected from a sample of 50 participants. The results revealed a significant correlation between the source of advertisement uploads and consumer perceptions of the products. Moreover, a relationship was found between personal conformity, social comparative factors, and perceptions of both celebgrams and the endorsed products. These findings highlight the substantial influence of the source of posts on consumers' perception of the products. Additionally, the research demonstrates that consumer perceptions of celebgrams play a pivotal role in shaping their perceptions of the endorsed products. These research findings have practical implications for marketing communication professionals utilizing social media platforms. By understanding the impact of celebgram endorsements on consumer perceptions, marketers can devise effective strategies to leverage social comparatives and personal conformity to enhance product awareness and influence consumer behavior.

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Revisiting the antecedent of electronic word-of-mouth (eWOM) during COVID-19 Pandemic

Cited by 9 publications

References 50 publications

Purchasing in the digital age: A meta-analytical perspective on trust, risk, security, and e-WOM in e-commerce

Purchasing in the digital age: A meta-analytical perspective on trust, risk, security, and e-WOM in e-commerce

Measuring Online Customer Satisfaction Based on Customer Reviews: Topic Modeling Method Using Latent Dirichlet Allocation (LDA) Algorithm

The Effect of Marketing Communication Strategies Through Celebgrams on Perceptions of the Product among Indonesian Millennials

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