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Acknowledgement: The University of Malta would like to acknowledge its gratitude to the European Commission, Joint Research Centre, Directorate-General for Research and Innovation, for their permission to upload this work on OAR@UoM. Further reuse of this document can be made, provided the source is acknowledged. This work was made available with the help of the Publications Office of the European Union, Copyright and Legal Issues Section. Pictures contained in the brochure may not be extracted and used independently ; The indicators in the table found in this book present a synthesis of research and innovation (R&I) performance in Malta. They relate knowledge investment and input to performance and economic output throughout the innovation cycle. They show thematic strengths in key technologies and also the high-tech and medium-tech contribution to the trade balance. The indicator on excellence in science and technology takes into consideration the quality of scientific production as well as technological development. The Innovation Output Indicator covers technological innovation, skills in knowledge-intensive activities, the competitiveness of knowledge-intensive goods and services, and the innovativeness of fast-growing enterprises, focusing on innovation output. The indicator on knowledge-intensity of the economy focuses on the economy's sectoral composition and specialisation and shows the evolution of the weight of knowledge-intensive sectors and products. ; N/A

This study investigates how local milieus foster innovation success of firms. We complement the common practice of linking firm performance indicators to regional characteristics with survey evidence on the perceived importance of locational factors. While the former approach assumes that location characteristics affect all firms in the same way, the survey allows us to model firms judging the attractiveness of locations by a heterogeneous set of criteria. It turns out that the availability of highly skilled labor and the proximity to suppliers matters for firms' innovation performance. Interestingly, location factors obtained from the survey provide a more accurate explanation on how local milieus facilitate innovation.

This paper explores technological trajectory transition in the perspective of innovation ecosystem and their effect on innovation performance of latecomers in market. A structural equation model is developed and tested with data collected from 366 firms in China. In specific, this paper categories technological trajectory transition creative accumulative technological trajectory transition (CCT) and creative disruptive technological trajectory transition (CDT). The results indicate that firms' organizational learning ability positively affect their technological trajectory transition and innovation performance. Firms' network relationship strength negatively affects their technological trajectory transition and positively affect their innovation performance. Governments' environmental concerns positively affect firms' technological trajectory transition and their innovation performance, whereas firms' environmental concerns do not. CCT does not positively affect their innovation performance. In contrast, CDT positively affects their innovation performance.

Despite of the deeply rooted belief of politicians from all over the world in the important role of Mittelstand firms, there has been surprisingly little empirical research on this issue, yet. This article contributes to the literature by studying whether the relative regional importance of Mittelstand firms has an effect on regional innovation performance. Using a cross section of German NUTS-3-regions, a significantly positive relation between the relative importance of owner-managed SMEs and patent applications is identified. This finding is highly robust when controlling for spatial correlations as they often occur in highly disaggregated regional analyses.

Innovation is one of the main determinants of economic development. Innovative activity is very complex, thus difficult to measure. The complexity of the phenomenon poses a great challenge for researchers to understand its determinants. The article focuses on the problem of innovation-related geographical disparities among European Union countries. Moreover, it analyses the principal components of innovation determined on the basis of the European Innovation Scoreboard (EIS) dimensions. The aim of the paper is to identify the principal components of the innovation index which differentiate countries by analysing the structure of the correlation between its components. All calculations were based on indicators included in the EIS 2020 Database, containing data from the years 2012–2019. A comparative analysis of the studied countries' innovation performance was carried out, based on the principal component analysis (PCA) method, with the purpose of finding the uncorrelated principal components of innovation which differentiate the studied countries. The results were achieved by reducing a 10-dimensional data set to a 2-dimensional one, for a simpler interpretation. The first principal component (PC1) consisted of the human resources, attractive research systems, and finance and support dimensions (understood as academia and finance). The second principal component (PC2), involving the employment impacts and linkages dimensions, was interpreted as business-related. PC1 and PC2 jointly explained 68% of the observed variance, and similar results were obtained for the 27 detailed indicators outlined in the EIS. We can therefore assume that we have an accurate representation of the information contained in the EIS data, which allows for an alternative assessment and ranking of innovation performance. The proposed simplified index, described in a 2-dimensional space, based on PC1 and PC2, makes it possible to group countries in a new way, according to their level of innovation, which offers a wide range of application, e.g. PC1 captures geographic disparities in innovation corresponding to the division between the old and new EU member states.

Abstract
Background and Purpose: The construct of organizational ambidexterity (OA) has attracted the growing attention in management research. Previous empirical research has investigated the effect of organisational ambidexterity on performance from various perspectives. This study aims to resolve the contradictory previous research findings on the relationship between organisational ambidexterity and innovation performance. We unpack this construct with combined dimension of ambidexterity, which relates to a combination of high levels of both exploration and exploitation (introduction of products or services that were new to the market and new to the firm).
Methodology: We frame our ambidexterity hypothesis in terms of firm's innovation orientation. The hypothesis is tested by using Community Innovation Survey (CIS) 2006 micro data at the organizational level in twelve countries. To operationalize an ambidexterity and firms innovation outcome, we used self-reported measures of innovativeness.
Results: To test our hypothesis, we developed a set of models and tested them with multiple hierarchical linear regression analyses. The results indicate that exploration and exploitation are positively related to firm's innovation performances which supports our assumption that both are complementary. Furthermore, we find that above and over their independent effects, through combining them into a single construct of organizational ambidexterity, this variable remains negatively and significantly related to innovation performance.
Conclusion: These results provides the managers with an idea of when managing trade-offs between exploration and exploitation would be more favorable versus detrimental. For firms with lower organizational ambidexterity, the relationship between exploration-exploitation and the firm's innovation performance is a more positive one.

PurposeIn today's knowledge economy the ability to innovate and develop new products is a key factor to sustain firm performance. Within this context, analysing the role of different components of intellectual capital (IC) becomes of foremost importance, as well as an under-investigated issue for small- and medium-sized enterprises (SMEs). The purpose of this paper is to investigate the impact of human, organisational and relational capital (RC) on radical innovation performance (RIP), as well as to examine whether organisational capital (OC) and RC mediate the relationship between human capital (HC) and RIP and whether OC moderates the relationship between RC and RIP.Design/methodology/approachThe methodology consisted of a factor analysis and different regression models to test for mediation and moderation. The analyses are carried out on a sample of 150 micro firms and SMEs involved in the production of machinery or instruments and located in Italy.FindingsResults show that HC is directly associated to RIP, as well as OC and RC that totally mediate the relationship between HC and RIP. Moreover, OC positively moderates the relationship between RC and RIP.Originality/valueThis study is particularly interesting because it adopts an overarching perspective on IC testing the interplay between the different components of IC. In addition, it focusses on the SME context which is under-investigated as far as IC and performance measurement is concerned.