The Moderating Role of National Culture on the Relationship Between Global Supply Chain Integration and Firm Performance in Nigeria

This study examines the moderating influence of national culture on the relationship between global supply chain integration and firm performance among Nigerian manufacturing and agro-processing firms. Supply chain integration, encompassing supplier integration, customer integration, and internal integration, has been widely demonstrated to improve operational performance and competitive outcomes in developed economy contexts. However, the extent to which cultural factors specific to the Nigerian business environment condition the supply chain integration-performance link has not been adequately investigated. The study employs a survey-based quantitative research design, collecting data from 180 operations and supply chain managers in manufacturing and agro-processing firms located in the South West and North West geopolitical zones through validated survey instruments. Structural equation modelling using partial least squares is applied to test the hypothesised relationships, with national culture operationalised through Hofstede's power distance and collectivism dimensions as measured through cultural value scales adapted for the Nigerian context. The theoretical framework draws on the relational view, resource-based view, and cross-cultural management literature. The study controls for firm size, industry sub-sector, and degree of export orientation. Findings are expected to reveal that high power distance cultural contexts moderate the supply chain integration-performance relationship by limiting information sharing willingness and supplier trust formation, while collectivist orientations positively moderate customer integration effectiveness. Contributions advance the understanding of cultural contingencies in supply chain management within Sub-Saharan African business environments. Keywords: national culture, supply chain integration, firm performance, Nigeria, structural equation modelling