Applying Artificial Neural Networks to Evaluate Export Performance: A Relational Approach
Applying Artificial Neural Networks to Evaluate Export Performance: A Relational Approach

Summary/Abstract: The paper applies artificial neural networks to investigate the effect of the exporter’s relationship orientation on the export performance, mediated by the relationship quality, taking into account the supplier’s strategic orientation and the foreign customer’s approach to purchasing. The proposed model is supported mainly by the Second Networking Marketing Paradox, the Commitment-Trust Theory, the Relationship Marketing Paradigm and International Marketing fundamentals. The model developed, proposes that an exporter’s relationship orientation influences the relationship quality with a foreign customer, which, in turn, influences the exporter’s performance. Furthermore, the model proposes that the content of the relationship orientation is contingent on either the company’s strategic orientation – internally defined – or the interface with the customer, which is external to the company’s decision-making. The results of the empirical study generally confirm the theoretical hypotheses.

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