You have probably noticed it yourself. You can get cheaper day passes for the alpine slopes if you book early. Or that skiing midweek can be cheaper than at weekends.
Why is this, and what do we think about it?
Per Kristian Alnes has tried to get closer to an answer in his doctoral thesis.
Two objectives and two pricing models
– Firstly, my aim with this work was to contribute to the price optimisation literature by introducing new time-based models for price differentiation, which take into account both demand shifts at different price levels and capacity constraints, writes Per Kristian to inn.no.
The two different pricing models he has based his work on are called Peak-load pricing and Early-bird pricing.
The first refers to setting prices higher during periods of high demand than during periods of low demand, while Early-bird pricing means offering a discount for booking in advance.
By demand shift, we mean that customers change their consumption patterns, buying the service at a different time if it saves them money.
– The second contribution I want my thesis to make is to offer new knowledge about customers' perceptions of fairness and their reactions to the introduction of time-based price differentiation, says Alnes.
The alpine skiing industry as an example
The empirical data he used was collected from the alpine skiing industry.
– This is an industry that typically experiences significant fluctuations in demand throughout a season. It is capital-intensive, with low variable costs and high fixed costs, says Per Kristian Alnes.
He then continues:
– Consequently, high capacity utilisation is important, and time-based price differentiation is a tool alpine resorts use to achieve this.
The significance of Peak-load pricing was analysed by setting a higher price for day passes at weekends than during the rest of the week, while Early-bird pricing was analysed by offering various discounts depending on how far in advance the day pass was purchased.
Per Kristian Alnes completed his PhD through the PhD programme Innovation in Services in the Public and Private Sectors (INSEPP).
The title of the thesis is 'Diversion and fairness perception in innovative pricing models'.
Main findings of the doctoral work:
- The models reveal that service providers need to consider both the diversion effect and the capacity constraints when setting optimal prices. The empirical results from the alpine sector confirm this.
- Diversion effects contribute to reduced price differences between weekdays and weekends and lower discounts for advance purchases.
- Early-bird discounts shall be set higher the longer the advance purchase period is.
- The willingness to pay for early-bird booking is generally highest in the local market.
- The capacity constraints significantly impact the intra-weekly price differentiation. The intra-weekly price differences increase with reduced capacity as long as the midweek capacity is not fully utilised.
- Framing the price change as an increase in the weekend price is perceived as less fair than framing the same price change as a reduced
- midweek price. In cases where an increase in the weekend price is necessary, the new (higher) weekend price should be presented as the new general day pass price and the midweek price as a discount.
- The magnitude of price differences between weekdays and weekends significantly negatively impacts perceived fairness. however, the marginal effects of discounts are low. Managers can, therefore, adapt the discount levels based on their price optimisation models without major concerns about how the discount level will affect the perceived fairness.
- Managers should not give discounts for shorter pre-booking periods if the firm is concerned with customer acceptance and fairness when
- implementing an early-bird pricing scheme. For longer time horizons, managers can set what they believe is the profit-maximising discount because the discount level has only a minor impact on perceived fairness.
Here you can find more information about Per Kristian Alnes's defence on the 1st of November, 2024
Contact information:
- per.alnes@inn.no
- Phone
- +47 61 28 84 01