Knowledge stocks have been identified as sources of competitive advantage. It is therefore critical for the organizations to understand the impact of knowledge stock accumulation (KSAC) on the performance of the firms. This study aims to explore the impact of KSAC in an International Joint Venture (IJV) context to develop a conceptual framework, and empirically test it. Existing studies are mainly cross-sectional in design and therefore, in contrast, this study adopts a quantitative longitudinal research design to enhance the understanding of the relationships among business relatedness of the parent firms (BRPF), KSAC, the organisational cultural difference (OCD), and international joint venture performance (IJVP). This study uses secondary data to quantify the variables. Specifically the primary aim of this study is to explore and validate the use of secondary data to instantiate the research in IJV context. For that ten waves of data (2006 to 2015) were collected from different databases related to 257 IJV deals. These IJVs have the parent firms (PFs) from UK or USA. Results showed that BRPF increases the KSAC of IJV, and KSAC influences the IJVP but KSAC mediates the relationship of BRPF and IJVP only in wave 10. Furthermore, OCD moderated the mediation effect of KSAC on IJVP. This study provides a new explanation of improved IJVP by recognising the importance of KSAC of the IJV and showing how increased KSAC leads to better IJVP. This study leads the use of secondary data in the IJV context and develop a conceptual model to for this which incorporates the mediating role of KSAC in the relationship of BRPF and IJVP and also the moderating role of OCD on the relationship between KSAC of the IJV and IJVP which was unexplored as well in the IJV context. The findings suggest that the improved KSAC of IJV can be explained by BRPF and the similarity of organisational culture (OC) and thus increase the performance of IJV. Naturally, using secondary data presents limitations in itself; an additional challenge explored is how to accommodate the use of proxies: for example, using normalisation to address the significant scale differences typically leads to a significant loss of statistical power. The managerial implications and suggestions for future research directions are also discussed in this study.