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p-Index From 2020 - 2025
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All Journal International Journal of Economics, Business and Innovation Research
Anggoro, Emi
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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The Role of Product Diversity, Brand Trust, and Price Fairness in Influencing Xiaomi Smartphone Purchasing Decisions Anggoro, Emi; Karnowahadi; Irin Mirrah Luthfia
International Journal of Economics, Business and Innovation Research Vol. 4 No. 05 (2025): August - September, International Journal of Economics, Business and Innovatio
Publisher : Cita konsultindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63922/ijebir.v4i05.2260

Abstract

This study was initiated in response to a drop in sales at Xiaomi Shop Fastronik Banyumanik for four months in a row, from July to October 2024. This study seeks to assess the impact of Product Diversity, Brand Trust, and Price Fairness on Purchase Decisions for Xiaomi Smartphones, focusing on consumers at Xiaomi Shop Fastronik Banyumanik. The data for this study was gathered through observations, questionnaires, and a literature review. The sample strategy employed was non-probability sampling utilizing a purposive sampling method. The study sample comprised 105 users at Xiaomi Shop Fastronik Banyumanik. This study employed data analysis techniques including validity testing, reliability tests, classical assumption tests, correlation analysis, coefficient of determination analysis, F-tests, and t-tests. This study employed IBM SPSS Statistics Version 26 for data processing. This study's findings demonstrate that product diversity, brand trust, and price fairness substantially affect purchasing decisions. Product diversity, brand trust, and price fairness account for 76.6% of the purchasing decision, but the remaining 23.4% is affected by additional variables not analyzed in this study. The t-test results demonstrate that the pricing justice variable exerts the greatest influence relative to the product diversity and brand trust factors. The regression equation derived from these results is Y = 0.561 + 0.238X1 + 0.318X2 + 0.420X3.
Co-Authors Irin Mirrah Luthfia Karnowahadi