An investigation into how B2B decision-makers utilise resources in their marketing decision-making
Everyone makes decisions, some simple, others complex. In business-to-business (B2B) marketing environments, decision-making becomes even more complicated. The decision-makers require an adequate set of facts to support their decision-making. In order to provide the necessary decision-support, B2B organisations invest huge amounts of money in information systems such as enterprise resources planning applications, customer relationship management software, and other types of databases. These systems store, analyse, manipulate and/or integrate internal data and perhaps force-feed it to the decision-makers; what we call a foie-gras approach. On the other hand, organisations may allow the decision-makers to search for the desired facts or decision-support by themselves; what we refer to as anarchic resources utilisation. Alternatively, the decision-makers may utilise resources with a combination of the two approaches. Previous studies have shown that many factors may influence the resources utilisation; however, not many studies have been conducted in the B2B context. This research, therefore, aims to provide a better understanding of how decision-makers utilise the available resources by firstly identifying B2B factors affecting the resources utilisation, and then explaining how these factors influence them. Results from in-depth interviews with the marketing decision-makers from three case studies show that the value of customers, supplier-customer relationships, and the nature of demand are the most influential B2B factors affecting the resources utilisation of the decision-makers. Other factors such as experience, nature of decisions, and management style are also found to have considerable impact on the approach the decision-makers adopt. In order to provide adequate decision-support, the providers may need to consider these factors and understand their effects on the decision-makers in the organisation, and design or choose the right information system(s); this should then result in better quality decisions.
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