Manager perceptions of big data reliability in revenue management.

This paper investigates the perceptions that managers have of the value and reliability of using big data to make hotel revenue management and pricing decisions. Whilst big data-driven automated revenue systems are technically capable of making pricing and inventory decisions without user input, the findings here show that the reality is that managers still interact with every stage of the revenue and pricing process from data collection to the implementation of price changes. They believe their personal insights are as valid as big data in increasing the reliability of the decision-making process. This is driven primarily by a lack of trust on the behalf of managers in the ability of the big data systems to understand and interpret local market and customer dynamics. The less a manager believes in the ability of those systems to interpret this data, the more they perceive gut-instinct to increase the reliability of their decision-making and the less they conduct an analysis of the statistical data provided by the systems. This provides a clear message that there appears to be a need for automated revenue systems to be flexible enough for managers to import the local data, information, and knowledge that they believe leads to revenue growth.