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The Effectiveness of the Affiliate Marketing Model in Enhancing the Competitiveness of MSMEs in the Digital Economy Era Andrianata, Mufid; suharsono, Judi; Wishal Nafis, Raihan; Fithrianto, M Novan
Jurnal Manajemen Dan Akuntansi Medan Vol. 7 No. 2 (2025): Jurnal Manajemen dan Akuntansi Medan Juli 2025
Publisher : Yayasan Cita Cendikiawan Al Kharizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jumansi.v7i2.6888

Abstract

The digital transformation has compelled Micro, Small, and Medium Enterprises (MSMEs) to adopt adaptive marketing strategies that align with shifting consumer behaviors. One such emerging approach is affiliate marketing, which leverages incentive-based partnerships to expand online product visibility. This study was conducted to explore the effectiveness of affiliate marketing models in strengthening MSME competitiveness amid the growing challenges of the digital economy. This research employed a qualitative approach with an exploratory case study design. Data were collected through in-depth interviews with MSME actors, limited participatory observation, and documentation of digital marketing practices. The data were analyzed thematically to identify recurring patterns, strategic applications, and the impacts of affiliate marketing adoption. The findings reveal that MSMEs which strategically integrate affiliate models experience significant improvements in market reach, sales performance, and brand image. The most effective strategies involve selecting affiliates aligned with specific market segments, producing platform-appropriate promotional content, and conducting regular performance evaluations. Additionally, affiliates contribute to market education and provide valuable feedback that supports ongoing marketing development. In conclusion, affiliate marketing models prove to be effective instruments for driving MSME digital transformation and sustaining competitive advantage. Future research is recommended to explore the long-term sustainability of affiliate partnerships, the role of AI-based analytics in optimizing affiliate selection, and comparative studies across sectors and regions within the Indonesian MSME landscape.
Penerapan Metode Altman Z-Score, Grover Score, Springate dan Zmijewski Untuk Memprediksi Potensi Kebangkrutan Suharsono, Judi; Rustianawati, Mutimmah; Febriani, Alvina; Fithrianto, M Novan; Andrianata, Mufid
eCo-Fin Vol. 7 No. 3 (2025): eCo-Fin
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/ef.v7i3.2411

Abstract

This research was conducted to determine the application of the Altman Z-Score, Grover Score, Springate and Zmijewski methods in predicting potential bankruptcy in food and beverage companies listed on the IDX for the 2021-2023 period. The type of research used is descriptive quantitative. Sample selection using purposive sampling method which resulted in 42 samples with 14 companies. The data used is secondary data, namely the company's annual financial statements food and beverage companies for the period 2021-2023. Data analysis is carried out by collecting financial statement data, calculating ratios, classifying company conditions, and comparing the results of the 4 methods. The results state that the Altman z-score method is the best method based on the ability to detect 4 companies that are at risk in the early stages (gray) before entering bankruptcy (dangerous), this can provide time for companies to improve their financial performance. springate method has 1 company that has gone bankrupt. this method only divides into 2 categories without a gray zone so it is less detailed in identifying early stage risks, while the grover score and zmijewski methods show the results of 14 companies in a healthy condition.