Imagine you fill up with 11.2 litres of petrol at the filling station and at the cash register you are charged 12 litres with the note: "We round up to the next litre. We would probably be surprised, as this rounding up leads to an actual price that is 7.14% (= 12 / 11.2 - 1) above the announced price. But are we as customers able to understand the effects of such rounding or is this kind of pricing deceptive?
Such a pricing model is rather unlikely for petrol stations, but it is very popular in many other industries. For example, car repair shops, lawyers or tax consultants usually use a quarter-hourly rate. Car parks or car-sharing service providers often charge by the hour. You even have to pay for your ski pass per day. In the past, this type of billing was also frequently used for mobile phone tariffs. Such clocking means that, as in the supermarket example, the provider charges for more use than actual use. Customers must therefore "buy one, pay two" if the billed usage is twice as high as the actual usage.
This happens, for example, if you leave the car park after only 30 minutes. At the same time, however, this also means that it is no longer so easy to calculate the invoice amount.In the article "Pricing Metrics and the Importance of Minimum and Billing Increments" by Bernd Skiera (Goethe University Frankfurt), Christian Schlereth (WHU - Otto Beisheim School of Management) and Sebastian Oetzel (University of Applied Sciences Fulda), which appears in the Journal of Service Research, the authors therefore examine the following research questions as examples for the telecommunications market:
- What influence does clocking have on usage and on the invoice amount?
- Do customers understand the influence of clocking on the invoice amount?
- What are the causes of tariff selection errors?
The analysis of over 700 mobile phone bills with almost 38,000 calls shows that the calculated usage is about 43% higher than the actual usage. This corresponds to about two thirds of the profits of the providers examined in the study. At the same time, it is unlikely that customers would adjust their usage behaviour if the providers were forced to charge by the second. In a survey carried out, a large number of unsystematic tariff selection errors can also be observed in hypothetical tariff selection decisions (approx. 48%). This corresponds roughly to the number of tariff selection errors in the transaction data (approx. 41%). The results of the survey also show that people who have problems understanding basic mathematical concepts are most likely to make a mistake when choosing a tariff.
You can find the article Open Access (available free of charge) here