Assessing the Impact of Laptop Condition on Pricing Using Statistical Analysis: Insights for Digital Marketing Strategies on eBay

Evelyn, and Suryodiningrat, Satrio Pradono (2025) Assessing the Impact of Laptop Condition on Pricing Using Statistical Analysis: Insights for Digital Marketing Strategies on eBay. Journal of Digital Market and Digital Currency, 2 (3). pp. 230-251. ISSN 3048-0981

Abstract

This study investigates the influence of laptop condition on pricing in the eBay marketplace, using statistical analysis to provide actionable insights for digital marketing strategies. The analysis is based on a dataset containing 2,952 laptop listings, categorized by condition into New, Open box, Excellent - Refurbished, Very Good - Refurbished, and Good - Refurbished. An ANOVA test revealed a significant difference in mean prices across these conditions (F-value = 76.69, p < 0.0001), indicating that condition is a critical factor in pricing. Post-hoc analysis using Tukeys HSD test further highlighted specific pairwise differences. For instance, the price difference between New and Good - Refurbished laptops was found to be approximately $192.66 (p < 0.0001), confirming that even minor wear significantly impacts consumer perception and pricing. Additionally, Excellent - Refurbished laptops were priced, on average, $62.79 higher than their New counterparts (p = 0.0008), suggesting a premium for well-maintained refurbished models. A multiple linear regression model was employed to quantify the impact of various factors on pricing, including condition, brand, RAM, and processor type. The model, with an R-squared value of 0.429, indicated that these variables collectively explain 42.9% of the variation in laptop prices. Despite the models moderate fit, the coefficients provided insights into the relative importance of each factor, with condition emerging as the most influential determinant. The findings suggest that eBay sellers should prioritize accurate and detailed descriptions of product condition to optimize pricing strategies. These results underscore the importance of condition-based pricing in digital marketing, offering a data-driven approach to maximizing profitability in online marketplaces.

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