When Revenue Management Algorithms go wrong!
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On the afternoon of 15th March, Brenton Tarrant enters Al Noor mosque in Christchurch, then onto Linwood Mosque and in the process kills 50 New Zealanders and injures another 50 using semi-weapons, shotguns and pistols. The largest and most deadly killings in New Zealand. Prime Minster Jacinda Ardern calls this ‘New Zealand’s darkest day’.
In Air New Zealand’s defence, the airline has responded by overriding the system and pegging airfares at NZ$139 for a one-way domestic fare to and from Christchurch and offered 100 bookings for free travel for immediate family members of victims and discounted compassionate fares for other affected friends and family…but only after a public outcry and intervention from the government minister responsible for the state airline.
All of this leads us to the role of perceived fairness and trust in revenue management (RM). Understanding customer behaviour and price elasticity is the core of RM. RM allows companies to charge the right price for a well-tailored product to each customer. However, there still remains a sense that RM is something that is done to customers rather that something that is done for the customer. Building mutual value into the relationship that companies have with their customers should, therefore, be one of the primary aims of any organisation. Revenue Management is adjusting prices to circumstances. When demand is high and capacity diminishing, price rapidly rises to sell the remaining seats. At the same time, when demand is low with an abundance of capacity, prices fall dramatically (McMahon-Beattie, McCentee, McKenna, Yeoman, & Hollywood, 2016)
One of the ways to build value is to establish a trusting relationship between buyer and seller. However, it could be argued that price discrimination, which is inherent in RM may undermine trust in an organisation where the customer perceives that they have been treated less fairly in terms of price than other buyers or when price is unjust.
Perceptions of trust and indeed fairness become a particular issue where modern IT-based systems of individual pricing allow multiple prices to be charged for ostensibly identical units of output, and where the results are less visible and may only be compared indirectly. This lack of openness in pricing creates conditions for mistrust. It is all black box science to the consumer. Openness is not apparent. Trust and mistrust go together with a degree of closeness. Thus RM has to be more than an algorithm. It needs a heart and a degree of compassion.