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This paper aims to study whether Peruvian manufacturing firms that implement innovation have positive performance and whether R&D activities moderate these relationships.

Using a data set of Peruvian manufacturing firms from the 2018 National Survey of Innovation, a LOGIT model analysis was applied to 774 companies. In addition, the authors fitted different models into subsamples to explore the moderating effects of R&D on manufacturing firms. Finally, the regression models were computed using R software.

The results indicate that product, service and marketing innovation are associated positively with an increase in market share, while process and organizational innovations are associated positively with productivity. Moreover, companies with R&D are more productivity-oriented than companies without R&D.

This study contributes to the literature on innovation management by supporting the assumption that innovation results in increased productivity and expands market demand. In addition, findings highlight that R&D is essential for boosting firms’ productivity.

Managers should consider an appropriate combination of the innovation portfolio and R&D investments to make progress and increase performance in the company. In addition, policymakers should consider that investments to promote the development of R&D activities in manufacturing companies will likely lead to médium- or long-term returns.

The correct use of indicators to measure these relationships could help the policymaker to design and measure policy instruments more efficiently.

These results provide a deeper understanding of how the effects of innovations implemented by manufacturing firms, especially service and process innovation, improve their performance.

This paper aims to focus on the effects of human capital composition, innovation portfolio and size on manufacturing firms’ performance. Moreover, it seeks to empirically identify the levels of education that are significant in labour productivity.

The resource-based view (RBV) theory is applied using data gathered from the National Innovation Survey in the Manufacturing Industries of Peru. Using the ordinary least squares method on a sample of 584 Peruvian manufacturing firms, the effects on firm performance of two subsamples according to innovation portfolio and firm size are determined.

The direct effects of human capital composition on productivity show that the higher the workers’ educational level, the higher the productivity. However, if this relationship is analysed in terms of the innovation portfolio, the authors find that labour productivity in companies with product–service innovation is greater (i.e. more significant) than in traditional manufacturing firms with only product innovations. Similarly, if this relationship is compared in terms of company, the authors find that large companies are more significant than small and medium-sized enterprises.

The study furthers the understanding of how the relationship between human capital composition, innovation portfolio and size of manufacturing firms positively affects labour productivity. Hence, it can help managers to craft their innovation portfolio according to the educational level of their human capital. This could require that not only human resource management innovates, but also that strategic partnerships be developed with educational establishments to boost training towards product–service innovation.

This study’s results provide confirmation that the configuration of human resources, innovation portfolio and size plays a significant role on manufacturing firms’ performance, particularly in the context of developing countries.

The purpose of this study is to identify the impact of intellectual capital on the innovation performance of the Jordanian banking sector and identify the moderating role of big data analytics.

For this study's purposes, 333 questionnaires were analysed. Convergent validity, discriminant validity and reliability tests were performed through structural equation modelling (SEM) in the Smart-PLS program. A bootstrapping technique was used to analyse the data.

Empirical results showed that each of the components of intellectual capital and big data analytics explains 63.5% of the variance in innovation performance and that all components of intellectual capital have a statistically significant impact on innovation performance. The results also revealed that the relationship between structural capital and innovation performance is moderated through big data analytics.

This cross-sectional study provides a snapshot at a given moment in time, a methodological limitation that affects the generalisation of its results, and the results are limited to one country.

This study promotes the idea of focusing on components of intellectual capital to enhance innovation performance in the Jordanian banking sector and knowing the effect of big data analytics in this relationship.

This study makes recommendations for financial policymakers to improve the effectiveness of intellectual capital practices and innovation performance in the context of big data analytics.

This study has important implications for leaders in the Jordanian banking sector, in general, as the study highlights the importance of intellectual capital to enhance the innovation performance, especially in light of the big data analytics in this sector, and thus increase the innovative capabilities of this banks, which leads to an increase in the level of innovation.