Abstract
Learning-by-searching is the process of experience in the emergence of new high-value-added products with the new knowledge and skills that an enterprise achieves through the network system it establishes with its own R&D unit, other enterprises, universities, and other information sources. The most important factor that contributes to learning-by-searching is undoubtedly the investments made in research and development in economic sectors. A review of the literature on the subject reveals that R&D expenditures are only used as the second independent variable in linear learning curve models. For this reason, in the existing applied studies, only a fixed representative learning rate, which is the average of the learning rates in the period in question, is determined. In this study, a two-factor dynamic learning curve model is used to measure the cost-reducing effect of R&D expenditures. Thus, in addition to learning-by-doing ratios, the evolution of learning-by-searching ratios over time is also taken into account. The findings of the study support the view in the literature that the learning-by-doing rates in the one-factor dynamic learning model are biased. In addition, in the two-factor dynamic learning curve model, it was also found that in periods when learning-by-doing loses its effect, learning-by-searching increases its effect.
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CITATION STYLE
Koç, A., & Yamak, N. (2025). The Contribution of R&D İnvestments to Technological Learning Capability: Evidence from Manufacturing İndustry Sectors of the Turkish Economy. WSEAS Transactions on Business and Economics, 22, 183–193. https://doi.org/10.37394/23207.2025.22.18
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