Conceptual arguments favouring a relational rather than a transactional approach to the study of buyer‐seller relationships are now well understood. However, attempts to quantify the factors contributing towards relationship quality have been held back by the complexity of the underlying factors and their interrelatedness. Traditional regression techniques are not effective in analysing data with high levels of multi‐collinearity and missing information, typical in many studies of buyer behaviour. Makes use of a relatively new technique – neural network analysis – to try to quantify the factors contributing to buyer‐seller relationship quality. The technique uses a statistically‐based learning procedure modelled on the workings of the human brain which quantifies the relationship between input and output variables through an intermediate “hidden” variable level analogous to the brain. For this study, a neural network was developed with two outcome components of relationship quality (relationship satisfaction and trust), and five input antecedents (the salesperson′s sales orientation, customer orientation, expertise, ethics and the relationship′s duration). In a comparison of multiple regression and neural network techniques, the latter was found to give statistically more significant outcomes. New applications within marketing for neural network analysis are being found. Contributes towards the development of the technique and suggests a number of further possible applications.

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Percentage of respondents 1-2 2-3 >3 Key Small mistake Big mistake Figure 3. Percentage of respondents still trusting their airline following a service failure Analyses of buyer-seller relationships Early stages of a relationship

The development of effective customer relationships is increasingly recognised as an important component of marketing strategies, particularly in the case of service industries. Developing and maintaining satisfactory customer relationships can help to reduce perceived risk, reduce transactions costs, increase customer loyalty and customer retention and thus impact on organisational performance. From the customer’s perspective, the determinants of relationship satisfaction are thought to include factors such as customer orientation, trust, length of relationship, expertise and ethics. Provides further evidence on the cognitive antecedents of relationship satisfaction based on evidence from the financial services sector.