As a result of globalisation of trade, the research on the role of global mindset (GM) in enhancing performance has gained momentum in the new millennium. Even though GM is considered as an essential prerequisite to performance in the current international business environment, the empirical evidence of the direct effects of GM on performance is mixed. One of the reasons for this mixed evidence is the existence of other mechanisms, such as mediators and moderators, which influence GM–performance relationships. This study focuses on one such mechanism, namely networks (NWs), and examines how NWs mediate the association between GM and the performance of the global grain and oilseed traders. The study argues that GM has little direct effect on trader performance (TP). Rather, GM strengthens network structure (NWS), which collectively leads to enhanced network leverage (NWL) and thus increased TP.

Based on a sample of 78 traders in the global grain and oilseed sector (GGOS), the study finds that both the network (NW) components – NWS and NWL – mediate the association between GM and TP. The finding of full path mediation provides empirical evidence that superior GM leads to superior NWS, which results in superior NWL and thus superior TP. The method used in data analysis is Partial Least Square Structural Equations Modelling (PLS-SEM), using SmartPLS software.

This study makes two main contributions. Firstly, the study endorses the critical role of GM in enhancing the performance of traders in the GGOS. Secondly, the study provides a deeper understanding of how GM enhances performance; that is, the serial mediating roles of NWS and NWL. The current research has largely suggested single mediation of relationship quality. This study goes a step further and introduces NWL into the argument. The key implications of the study include the need to strengthen the GM and NWs of traders, as the interplay between the two is critical in enhancing their performance. The findings need to be interpreted carefully, as the study suffers from limitations of small sample size and single sector study