Abstract
Although Türkiye is among the leading producers of cherries worldwide, its export performance does not fully reflect its production potential. This gap points to the importance of understanding how trade incentives, destination-market demand, and trade costs shape export outcomes in high-value horticultural products. This study investigates the determinants of Türkiye’s fresh cherry exports during 2015–2023 by combining a gravity trade model with machine learning approaches. The empirical framework incorporates export support mechanisms, macroeconomic indicators of partner countries, import demand, and geographical distance between Türkiye and its trading partners. It was found out that trade incentives have a positive effect on cherry exports; showing support mechanisms can strengthen Türkiye’s competitiveness in international markets. The findings also reveal that rising import demand in destination countries stimulates exports, while geographical distance and adverse changes in importer income conditions limit export performance. These results suggest that maintaining export incentives alone may not be sufficient; rather, support policies should be adjusted according to market-specific demand conditions, income dynamics, and trade-cost factors. By integrating policy variables with destination-market characteristics, this study provides empirical evidence for designing more effective export support strategies for Türkiye’s cherry sector.