Relationship Between Millennials and Brand Loyalty: Mediating Brand Loyalty Factors

Dhameeth, S. Gehan; Ochi, Yamamoto

doi:10.22158/jbtp.v5n3p223

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…It correlates with customer retention, loyalty, and financial performance [19]. Customer satisfaction results from assessing the rewards and costs of purchase compared to expectations, acting as a bridge between expectations and perceived product performance [20][21][22]. Bhattacharya et al identify two levels: micro (intrinsic) linked to individual perception and macro (extrinsic) compared with competitor offers [1].…”

Section: • Customer Satisfactionmentioning

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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Section: • Customer Satisfactionmentioning

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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“…Hence, their use of self-service technology, that allows to avoid human interaction, is higher (Mayock, 2014). In addition, being a Millennial is positively related with being loyal toward brands (Gehan and Yamamoto, 2017).…”

Section: Introductionmentioning

confidence: 97%

Do Millennials differ in terms of survey participation?

Bosch¹,

Revilla

Paura³

2018

International Journal of Market Research

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Millennials have been the focus of quite some research because of their differences with older cohorts. Besides, young respondents have been considered as a hard target population for surveys. However, to our knowledge, no research has compared the levels and types of survey participation of the Millennials versus the older generations. Using a dataset of 1,570,301 panelists of an opt-in online panel in eight countries from Europe, Latin America, and North America, we show that Millennials differ from older cohorts in terms of survey participation. Millennials show lower participation rates than older cohorts. Moreover, they present significantly higher proportions of surveys answered using smartphones. However, differences across cohorts in terms of break-offs and survey evaluation are mainly nonsignificant and/or nonmeaningful.

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