# Risk assessment and decision-making

###### Pedro Moreira | December 4, 2018

How do we decide? What shapes our decisions? Are our decisions mainly deliberative and rational? Or do we act on our feelings? Today, we will share with you an overview of the building blocks associated with decision-making processing.

Decision-making involves the ability to choose from different available alternatives on the basis of a subjective value. These processes are widely spread in nature, ranging from basic primitive behaviors to more complex decisions. As humans, we decide within a variety of contexts, including voting, gambling, shopping, deciding whether to go on a date with someone, or what to order in a restaurant.

According to Rangel and collaborators (2009), any decision involves a sequence of different phases, where the individual first represents the set of alternatives for a given decision-making scenario (the representation phase – *what are the different alternatives for choosing?*) and assigns a value to each action (the valuation phase – *what is the value of each action?*), which will guide the choice of an alternative (action selection – *based on the set of alternatives, I choose the option A*). Finally, the individual will evaluate the consequences of the action by assessing the outcome (outcome evaluation phase – *how desirable are the outcomes?*) which will be used for updating the representation, valuation and action selection of decision-making scenarios (learning phase).

*Adapted from Rangel et al (2009)*

As we decide, we expect a given outcome. However, the action-outcome associations are probabilistic, which means that most decisions involve some level of risk. This is particularly evident in gambling scenarios, where we play with monetary outcomes, such as lotteries or sports’ bets. Let’s focus on such examples. Imagine the following scenarios, where you are given the option of choosing between two options that may or not yield a monetary gain or loss. Please consider each scenario carefully and think about the options you would take.

***

__Scenario 1__

**Option A**: sure winning of 10.000€

**Option B**: 50% chance of winning 30.000€.

Which option would you choose?

***

__Scenario 2__

**Option A**: 1% chance of winning 30.000€

**Option B**: 2% chance of winning 10.000€.

Which option would you choose?

***

__Scenario 3__

*Option A: sure loss of 10.000€*

*Option B: 50% chance of losing 30.000€*

Which option would you choose?

***

According to a vast body of psychological research, if you are like most people, you probably choose option A for scenarios 1 and 2 and option B for scenario 3. If we multiply the total amount of the monetary gain by the probability of actually getting it to get the expected value, we observe that the most optimal choices would be different.

***

__Scenario 1__

Option A: 1*10.000 = Win 10.000€

**Option B: 0.5*30.000 = Win 15.000€**

__Scenario 2__

**Option A: 0.01*30.000 = Win 300€**

Option B: 0.02*10.000 = Win 200€

__Scenario 3__

**Option A: 1*10.000 = Lose 10.000€**

Option B: 0.5*30.000 = Lose 15.000€

***

As represented, the expected value would be greater for Option B, considering scenario 1, and for Option A, considering scenarios 2 and 3. So, what is driving the differences between the actual responses and those with higher expected values? According to the expected utility view, people are supposed to decide in a consistent fashion, by choosing the alternatives leading to the maximum expected utility and that those choices will be consistent across individuals. The very first message to highlight is that individuals are not consistent, rational decision-makers. A review of the behavioral economics literature reveals that when people are confronted with similar choices between two gambles, their decisions will differ in approximately 25% of the cases. Furthermore, at the end of the 70s, Daniel Kahneman and Amos Tversky developed a seminal work that influenced the dominant perspective of how a human makes a decision – the Prospect Theory. According to this view, people seem to distinguish differentially the variation of probabilities for high and low probabilities – we tend to prefer choices with very high probabilities of return over choices with lower probabilities of success even if the expected value of the choice of lower probabilities is higher. On the other hand, when dealing with low probabilities of success, people tend to prefer the choices with a higher return. As humans, we attribute more weight to right-skewed probabilities, which justifies why we tend to be attracted by gambles in which we invest a little with a very low probability of winning a lot. Second, people weight differentially losses and gains when faced with similar pairs of choices – human beings typically display a risk-seeking profile when the options are presented as potential losses while having risk-aversion decisions for options potential gains. The reason behind this relies on the fact that, as humans, we feel a more psychological impact for losses than gains, which means that we feel more pain when we lose than we feel pleasure when we gain.

*Source: http://fqmom.com/loss-aversionthe-psychology-money-series/*

Next week, we will discuss the association between decision-making under risk and emotional arousal. We will summarize the findings from the literature to give you an overview of how psychophysiological responses are associated with risk-seeking and loss-aversion.

###### Pedro Moreira

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