Location of a multinational corporation in a cluster A theoretical model of knowledge transfer

Purpose - A multinational company (MNC) looking to locate within a cluster is mainly interested in gaining access to scarce and highly valuable tacit knowledge. The transfer of such resources first requires sharing a certain degree of architectural and specific knowledge. This paper aims to examine the transfer of systemic technological expertise (specific tacit knowledge) that is incorporated into organisational practices (architectural knowledge). To quantify the level of knowledge transfer involved, the present study defines the architectural distance between the MNC and the cluster. Design/methodology/approach - The mathematical expression of acquisition performance is inferred from a conceptual study that formulates hypotheses regarding the impact of these variables on knowledge transfer. The MNC chooses its location in such a way as to maximise this performance. Findings - Applying a mathematical model to knowledge transfer between two of the MNC units helps to determine if the locally acquired knowledge could benefit other units of the MNC. Research limitations/implications - The present study defines the architectural distance between the MNC and the cluster. This architectural distance is defined by a vector composed of social, organisational, cultural, institutional, technological and geographic distances between the new acquisition and its network of local partners, on the one hand, and the MNC, on the other. Knowledge transfer also depends on the business players' trust and motivation. Further research through a quantitative study would be useful to improve the links between the proposed mathematical model and the efficiency of an MNC's location within a cluster. Practical implications - The solution to the optimisation problem allows to put forward a simple decision criterion to assist a manager who has to face the problem of an optimal location choice. Originality/value - First, this study contributes to a better understanding of how knowledge transfer effects may interact with cluster effects, while explaining a subsidiary's performance with regard to location. Second, it provides an interpretation of the concept of knowledge embeddedness by showing that the effective transfer of architectural and specific knowledge involves the prior sharing of a certain amount of this knowledge.