This study applied artificial neural networks to explore the influences of the quantitative and qualitative patent indicators upon corporate market value in the US pharmaceutical industry. The results showed that US pharmaceutical companies should not concentrate most of their R&D resources on one particular technological field, but create wider technological capabilities to avoid missing new technological opportunities and to decrease the risk of the lock-in effect. Moreover, in order to enhance their market values they should invest more resources in R&D activities to increase their advantage in their most important technological fields. In addition, this study found out that patent citations have an inverse U-shaped influence upon corporate market value and there exists an optimal value for patent citations. If patent citations are below the optimal value, they are positively associated with corporate market value. However, if patent citations are beyond the optimal value, they are negatively associated with corporate market value because of the significant spillover effect of R&D in the pharmaceutical industry.
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Chen et al. (2010) studied this question.