Integrating Price Sensitivity and Social Media Marketing to Predict Consumer Purchase Decisions in Tourism Packages
DOI:
https://doi.org/10.53905/Gimer.v1i03.24Keywords:
price sensitivity, social media marketing, purchase decision, tourism packages, consumer behavior, digital marketingAbstract
Purpose: This study investigates the impact of price sensitivity and social media marketing strategies on consumer purchase decisions for holiday packages in the Indonesian tourism sector, specifically examining PT Bangben Group Indonesia's operations.
Materials and Methods: A quantitative research design was employed with a population of 417 holiday package consumers during 2024. Using Slovin's formula, 81 respondents were selected through random sampling. Data collection utilized structured questionnaires measured on a 5-point Likert scale. Multiple linear regression analysis was conducted using SPSS version 22 to examine relationships between variables: price (X₁), social media marketing (X₂), and purchase decisions (Y). Validity testing employed Pearson correlation (r > 0.218), while reliability was assessed using Cronbach's alpha (α > 0.60).
Results: The regression model Y = 6.888 + 0.764X₁ + 0.635X₂ + e demonstrated that both price and social media marketing significantly influence purchase decisions. Price showed positive significant effect (t = 3.616 > t-table 1.991, p = 0.001), as did social media marketing (t = 4.402 > t-table 1.991, p = 0.000). The simultaneous effect was confirmed (F = 52.730 > F-table 3.11, p = 0.000). The adjusted R² of 0.564 indicates that 56.4% of purchase decision variance is explained by these variables.
Conclusions: Price sensitivity and social media marketing are critical determinants of consumer purchase decisions in tourism packages. The stronger influence of social media marketing (β = 0.452) compared to price (β = 0.371) suggests shifting consumer priorities in digital environments. Tourism operators should integrate competitive pricing strategies with robust social media presence to optimize conversion rates.
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