Arifuddin Arifuddin
Faculty of Engineering, Universitas Ichsan Gorontalo Utara

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PRODUCT QUALITY STRATEGY AND E-COMMERCE UTILIZATION ON PURCHASE DECISIONS AMONG MSMES IN NORTH GORONTALO La Diu Samiu; Muhammad Annas; Arifuddin Arifuddin
Jurnal Ilmu Ekonomi dan Pembangunan Vol 26, No 1 (2026): Jurnal Ilmu Ekonomi dan Pembangunan
Publisher : EP FEB UNS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jiep.v26i1.117719

Abstract

The increasingly widespread adoption of e-commerce among micro, small, and medium enterprises (MSMEs) in developing regions raises empirical questions about the extent to which product quality improvement strategies and the use of digital platforms influence consumer purchasing decisions. This study aims to examine the influence of product improvement strategies (X1) and e-commerce market potential (X2) on purchasing decisions (Y) among MSMEs in North Gorontalo Regency, Indonesia. A quantitative approach was used as the primary method, supplemented by qualitative data to enrich contextual interpretation. Data collected through a structured questionnaire administered to 100 MSME respondents purposively selected based on the criteria of actively using e-commerce platforms were then analyzed using multiple linear regression through SPSS version 26. The results of the analysis showed that neither X1 (β = −0.169; p = 0.521) nor X2 (β = −0.235; p = 0.397) had a statistically significant influence on purchasing decisions. The test also yielded an insignificant simultaneous value (F = 1.326; p = 0.287), with the model's ability to explain limited variance (R² = 0.112; Adjusted R² = 0.028). These findings indicate that product improvement strategies and e-commerce market potential, as operationalized in this study, have not been proven to be the main determinants of purchasing decisions in the context of MSMEs in areas with limited digital infrastructure. Future research should consider additional variables such as digital literacy, price, and service quality to improve the model's predictive power.