This paper examines the benefits of and barriers to technology transfers from academia to industry perceived by entrepreneurs and particularly associated with the dimensions of Entrepreneurial Capacity. This study is one of the first in which the analysis of the topic goes beyond the high-tech sectors. It is based on a survey of representatives of Small and Medium Enterprises (SMEs) dedicated to the production of Leather and Footwear in Peru. The main findings were that the Absorption Capability dimension had a positive relationship coefficient with the understanding of the benefits of and barriers to technology transfers, while the Networking Diversity dimension presented a negative relationship coefficient. Likewise, this study shows that the main barriers to technology transfer were the fear of information leaks and the lack of training. The results of this research can add value to decision makers in industry, academia, and government agencies interested in science and technology policies.

For years, the appropriate interpretation and application of metrics have enabledscientists to assess science and technology dynamics. Consequently, diverse disciplines haveemerged, such as bibliometrics, scientometrics and patentometrics, offering importanttheoretical and methodological contributions. However, the current accelerated technologicaladvances require researchers to implement a superior approach to detect continuous changesin the external environment identifying opportunities and vulnerabilities to strengthen thedecision-making process regarding R&D and innovation. In this context, competitive technologyintelligence (CTI) offers a strategic approach based on a continuous cycle where information istransformed into an actionable result. This research provides a broader scope to science andtechnology metrics, incorporating them into a CTI global methodology of eight steps. Metricsadd value throughout the entire CTI process, from project planning to decision-making stages,having the most significant role in the information analysis stage, mainly to process informationfrom sources such as scientific documents, patents, and social networks. Particularly, thisapproach considers recent studies in CTI in which quantitative tools such as patentometricsand scientometrics were successfully used. This proposal can be applied to predict upcomingtechnologies, movements of competitors, disrupting activities, market changes, and futuretrends. Accordingly, this research adds value to the assessment of science and technologydynamics, aiming to improve the decision-making process of R&D and innovation.