Analyzing Repurchase Intentions of Lipstick using Binary Logistic Regression
-
Ayu Wulandari
*
Universitas Bakrie, Jakarta,
Indonesia
- E N Budiyanto Hariandja Universitas Bakrie, Jakarta, Indonesia
- Annisa Liestiani Universitas Bakrie, Jakarta, Indonesia
- Jerry Heikal Universitas Bakrie, Jakarta, Indonesia (*) Corresponding Author
Abstract
This study aims to examine the various factors influencing consumers repurchase decisions for Wardah Lipstick. The research employs binary logistic regression using the SPSS software as the analytical tool. A total of 109 respondents were randomly selected, the collected data was first organized in Microsoft Excel and then normalized. Text-based responses for the independent and dependent variables, were converted into binary values, where 1 represents "Yes" and 0 represents "No". The independent variables examined in this study include Sufficiently Many Variants and Color Options, Reliable Product Quality, Well-Known Brand, Prestigious Brand Image, Availability of New and Innovative Products, Personal Interest in New Product Types, Affordable Price, Competitive Price Compared to Others, Price Matches Product Quality, Good Value for Money, Ease of Access to Store Location, Product Availability at Point of Sale, Past Positive Experience or Brand Recall, Recommendation from Friends, Recommendation from Family, Influencer Recommendation, Promotion via Facebook, Promotion via Instagram, Promotion via X, Promotion via YouTube, Promotion via Website, Satisfaction with Wardah Counter Service, Attractive and Functional Packaging and Easy-to-Remember Brand Identity. The dependent variable in this study is repurchase intention. The findings indicate that “Sufficiently Many Variants and Color Options” and “Reliable Product Quality”, are the most significant factors influencing consumers decisions to repurchase Wardah Lipstick. Other variables were found to have no substantial impact on repurchase behavior. Based on the binary logistic regression analysis of 109 Wardah consumers, the model predicts that 94 consumers are likely to repurchase the product, while 15 consumers are not, with an overall predictive accuracy of 88.1%.
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References
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