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Effect of Affiliate Marketing on the Performance of Selected Small and Medium Automobile Enterprises in Nairobi City County, Kenya

Year: 2026
Type: article
Abstract: Purpose: This study examined the effect of affiliate marketing on the performance of selected small and medium automobile enterprises in Nairobi City County, Kenya. Methodology: Anchored on the Balanced Scorecard framework, the study adopted a descriptive research design. A census approach targeted 130 respondents drawn from 65 automobile SMEs. Primary data were collected using structured questionnaires administered through the drop-and-pick technique. Data were analyzed using descriptive and inferential statistics, with regression analysis applied to test the relationship between affiliate marketing and firm performance. An overall response rate of 86.7% was achieved, ensuring reliability of the findings. Findings: The results revealed that affiliate marketing had a strong, positive, and statistically significant effect on SME performance (β = 0.511, p < 0.001). The model explained 42.3% of the variation in performance, indicating that firms implementing structured affiliate programs experienced increased profitability, enhanced market reach, improved customer retention, and stronger competitive positioning. Unique Contribution to Theory, Practice and Policy: The study extends the application of the Balanced Scorecard to digital partnership strategies in emerging economies by empirically linking affiliate marketing to multidimensional SME performance. Practically, it provides a strategic pathway for automobile SMEs to formalize affiliate programs and invest in digital collaboration capabilities. From a policy perspective, the findings support the development of frameworks that promote performance-based digital marketing adoption among SMEs. Keywords: Affiliate marketing, SME performance, automobile enterprises, digital marketing, Balanced Scorecard, Nairobi City County.
DOI: 10.5281/zenodo.18728997
Institution: Kenyatta University
Language: English
Open Access status: green
OpenAlex ID: W7130988295
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