Purpose This study aims to analyse the complementary role of structural and relational capital (as the outcomes of codification and personalisation knowledge management strategies) in renewal capital and innovation in high- and low-tech companies. Design/methodology/approach The primary data, which were collected through a structured questionnaire from 180 Spanish companies, are analysed using structural equation modelling based on partial least squares. Findings Overall, the study offers three fundamental findings. First, it demonstrates the outstanding role of renewal capital as an intellectual capital (IC) component; second, it provides a conceptual analysis of the connection between knowledge management strategies and IC; and third, it highlights the necessity of considering the technological level of the firm as a contingency variable affecting the IC–innovation relationship. Research limitations/implications The study has three apparent limitations: The sample of firms is restricted to Spanish companies, data concerning the main study variables were collected from only one person at each firm, and not all of the possible components of IC were included in the research model. Practical implications Business practitioners can find useful guidelines for making efficient use of knowledge resources when boosting innovation performance, depending on the technological level of their firms. Originality/value Although many studies have tried to disentangle the IC–innovation connection, this study is unique, as it considers knowledge management strategies, a novel combination of IC components and the level of technological sophistication in the same analysis.

If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. Research limitations/implications -The estimation procedure allowed only a partial validation of the proposed model because, although positive, the relationships between MAS and RC, between HC and performance and between RC and organizational performance were not statistically significant. Practical implications -The study highlights the role of MAS as information networks that collect, process and communicate information that influences the development of IC, as well as networks of relationships that support the establishment of conditions for the creation and integration of organizational knowledge and the development of IC. Originality/value -In this research, an arguably more complete framework of the relations between MAS, IC and performance is developed and empirically tested. Despite the existence of some literature addressing the relationship between MAS and IC, this is the first study, of which authors are aware, that focuses specifically on the relationships between MAS and the three dimensions of IC (HC, SC and RC), as well as their effects on organizational performance.

There is widespread understanding that intellectual capital (IC), consisting of the valuable knowledge resources of an organization, is a key enabler of innovation activities; however, little is known about the more specific contingencies impacting the relationship between IC and innovation. Thus, this article examines firm technology level and innovation type as contingency variables. It was argued that because high‐tech and low‐tech firms differ in terms of several knowledge characteristics (complexity, tacitness and pace of renovation), it is likely that their innovation performance is supported by different combinations of IC components. Furthermore, differences between product/service and managerial innovation could also lead to changes in the degree of relevance of various IC components. To test these contingency hypotheses, a survey dataset collected from 180 Spanish companies is analysed using structural equation modelling. The results demonstrate that both firm's technology level and type of innovation affect how IC influences innovation performance. The findings contribute to a knowledge‐based perspective on innovation and pave the way for a more context‐sensitive and contingency‐mindful approach to understanding innovation and knowledge‐based value creation.