A while back I read the widely known book by nobel laureate Daniel Kahneman “Thinking fast and slow”. In it he describe a psychological heuristic called peak-end rule. It describes the observation that people’s perception about an activity depend heavily on how they experience its end rather than say the sum of or the average moment of the experience.

Kahneman and his associates published a study in 1993 with the titled “When More Pain Is Preferred to Less: Adding a Better End”. In a wikipedia article, the experiment they conducted is described in the following way:

Participants were subjected to two different versions of a single unpleasant experience. The first trial had subjects submerge a hand in 14 °C water for 60 seconds. The second trial had subjects submerge the other hand in 14 °C water for 60 seconds, but then keep their hand submerged for an additional 30 seconds, during which the temperature was raised to 15 °C. Subjects were then offered the option of which trial to repeat. Against the law of temporal monotonicity, subjects were more willing to repeat the second trial, despite a prolonged exposure to uncomfortable temperatures.”


The participant’s remembered the second trial more favourably even though they experienced unpleasing temperatures for a longer period. This finding have very practical applications in many areas such as business, health care and even dating. The ending of a customer interaction will be highly influential for whether or not the customer will come back to your business in the future. By making the ending of a painful medical treatment slightly less painful, patients will have a better experience, and perhaps have an easier recovery. If you want to maximise your chances of getting that second date, don’t argue over whether or not you should split the bill after the restaurant visit on the first date.

Applied to game economics, this means player’s opinion of a video game will be highly influenced by the ending of the gaming sessions, rather than the overall playing experience. Now what makes someone stop playing a certain game? The economists way of thinking about this is to think about decision making at the margin.

Suppose we are talking about a game that isn’t continuous but consists of subgames such as battlefield, or dota where players play matches. After each match, the player will make an inner calculation whether to play another game or not. As long the marginal benefit is higher than the marginal cost, they will continue playing. This means there’s a great chance that the last match that they play each session is the one that gives least satisfaction (if there’s decreasing marginal utility from playing video games). Considering the peak-end rule, this is not at all optimal.

If a gaming session is disrupted by an exogenous factor (for example because the player’s parent demands they go to bed because it’s weekday and they have school tomorrow), the player might get a more positive view of the game than if the player is (a grown up and) allowed to play however much they want and so play until they grow tired or bored.

If game developers deliberately create game session disrupting elements in the game, it’s possible that total amount played will increase. In other words, even though each session is cut down before the player themselves chooses to stop playing, increased number of gaming sessions may lead to a larger total playing time – and a better playing experience.

Creating session disruption elements in a game might be a sensitive thing to do however, and different individuals may respond differently to such mechanisms. In freemium games, only allowing players to play for a limited time (for free) can be one way of doing this. Including natural waiting periodsis another way (in Simcity BuildIt, players have to follow specified time schedules to harvest/farm/cash in on resources and so continue playing).

This is a hypothesis still. But a testable one! As I’ve written before, video games are the perfect environment for social science randomized controlled trial experiments. Here’s one thing that would be cool to test.

Comments (1)

  1. Phil


    Let’s say this holds (isn’t there opposing research on first impressions?). Aren’t we in a paradox: if I just had a really good experience why would I stop? Game are like the mouse experiment on pleasure, pull a lever, get some endorphins. They aren’t fixed pieces of content like movies, the player gets to choose his/her session length.

    Let’s then say we employ a timer, like you suggest. What is the optimal length? Should the timer out last for 1 hour or 3? Maybe 8 days? What factors influence the optimal timer length?

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