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CRISIS EFFECTS ON RATIONAL AND SELF-INTERESTED CONSUMER CHOICE

UNIVERSITY OF AMSTERDAM

30-06-2021 Student: Al Naji

Student number: 12958999 Supervisor: Dr. H. Fasaei

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Content

1. Introduction ... 4

2. Literature review ... 8

3. Data and Methods ... 24

4. Results... 30

5. Discussion ... 40

6. Conclusion ... 42

7. References ... 43

8. Appendix ... 47

Statement of Originality

This document is written by Student Al Naji who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

Signature: A. Naji

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Abstract

One of the benefits of assumptions in neoclassical economics is that it helps to understand choices that individuals make. It assumes rational choices, perfect information, and profit maximization, which define the homo economicus (Thaler, 2016). However, the assumptions of economic theory and knowledge within psychology differ from each other quit a lot (Kahneman, 2003). Therefore, behavioral economists disagree with the notion that people behave like typical homo-economicus (Sen, 1977). Furthermore, existing literature confirms that consumer behavior is influenced by external and internal factors (Schiffman et al., 2012).

Nevertheless, contributions to the effect of something severe as a crisis on the rational and self- interested behavior of consumers specifically seems scarce. Similar to prior behavioral research, the main goal of this paper is to provide concrete evidence that will help develop economic theory. A research is conducted with the use of an experimental survey completed by 115 Dutch respondents. Game theory serves as a foundation for the expectations of the experiment. Most of our findings confirm prior dictator game and ultimatum game experiments.

Even though we know that external and internal factors influence consumer choice, we did not find evidence that a crisis significantly influences consumer choice in our experiment. Overall, our experimental study findings support the assumptions of behavioral economic theory, demonstrating that individuals do indeed act irrationally and make self-less judgments, even when the stakes are high, and a crisis arises.

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1. Introduction

“No one seriously believed that all people have rational beliefs and make rational decisions all the time” (Kahneman, 2003).

Existing literature from behavioral economics puts much emphasize on discrediting the idea that people behave like rational, self-interested, and utility-maximizing individuals (Sen, 1977). As a result, we find various examples and experiments that show the behavior of individuals to be the opposite of these characteristics that describe a typical homo economicus (Thaler, 2016). However, research on what type of situations does make people act more individualistic, rational and profit maximizing appears to be inadequate in the field of behavioral economics. This is remarkable because the concept of homo economicus or “econs”

plays an important role in economic theory (Gintis, 2000) and is in fact one of the main assumptions in neoclassical economics (Kahneman, 2003). This paper aims to investigate this field and provide clarity to what extent econ-type behavior is influenced by external economic factors.

The Covid-19 pandemic has disrupted the consumer habits of buying as well as shopping (Sheth, 2020). This paper tries to identify whether such a crisis also strengthens rational and self-interested behavior. It is known that various internal and external factors influence consumer behavior (Ramya, 2016) as consumers decrease spending and increase savings during crisis (Filip, 2011). Furthermore, we have all observed the sudden rush of selfish behavior during the Covid crisis as many people started hoarding supermarkets. Hoarding is an obvious example of selfishness during crisis which we also observed in previous crises (Higgins, 2013).

However, there are contradicting examples such as social interest appearing to overpower self- interest. For instance, the well-known “support your locals” initiatives worldwide show charitable behavior towards other businesses. But to what extent charitable behavior is truly

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selfless is difficult to confirm (Miller, 2001). This leaves the matter whether crises therefore influence people to become more self-interested and rational. If that is the case, we could argue that a crisis triggers people to indeed act more like econs.

Reviewing present literature, a gap was identified in the effect of external economic factors on the rational and self-interested behavior of individuals. Currently there exist two main views.

First, traditional economics assume that all people simply act as homo economicus or “econs”

in any situation (Gintis, 2000). Meanwhile, behavioral theorists are mainly concerned with proving such an assumption is neither correct nor realistic and that we should focus more on behavioral economics (Powell, 2011). According to behavioral theorists, humans are irrational and act and run by biases in their decision making (Kahneman, 2003).

The goal of this paper is to research a situation in which both traditional economic theorists and behavioral theorists can agree upon the standard assumptions of human behavior.

Therefore, this paper tests whether the traditional economic assumption of homo-economicus does hold in crisis situations. This can be done by exploring the deviations of expected economic theory behavior which may provide concrete evidence that will help develop economic theory (Camerer & Thaler, 1995). Current behavioral theory misses data on the role that a crisis might play in fostering selfish and rational behavior. Early theories of consumer behavior were also based on economic theory, assuming that people act rational and are maximizing their benefit (Schiffman, 2012). Even though we know that that situational factors, outside personal traits, influence consumer behavior (Belk, 1975), there seems no to little theory in the field of traditional economics, behavioral economics or consumer behavior that assesses the effects of external economic factors (like crises) on the rational and self-interested behavior of people. We aim to explore this phenomenon and address this research gap by asking:

To what extent does a crisis influence people to act more self-interested and rational in terms of consumer decision making?

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We aim to make several contributions to managerial practice and behavioral research.

Currently there are no immediate prospects of economics and psychology sharing a common theory of human behavior (Kahneman, 2003). Therefore, with this paper we try to move away from a too narrow view that currently exists in traditional economic theory as a threat (Powell, 2011). We do this by adding more nuance in behavioral and standard economic theory. Based on the literature we can argue that people are not fully rational and self-centered in regular situations (Kahneman, 2003; Thaler, 2016; Powell, 2011). Nevertheless, this paper tests whether the traditional economic assumptions about rational and selfish behavior do prove to be accurate in critical situations. We have reason to think so based on earlier findings (Dasgupta, 2020; Higgins, 2013) and our observations during the Covid crisis. However, these studies where not specified towards finding a correlation between a crisis and rational or selfish behavior. This paper’s main objective is to research such a possible correlation and contribute to the field of (behavioral) economics and consumer behavior research.

Furthermore, in behavioral economics, experiments that build on one another are used to reveal a radically different view of how people make decisions compared to the standard assumptions (Harvard Business Review, 2009). With this paper we aim to strengthen the external validity of behavioral economics by conducting similar experiments in a different setting. When looking at the original dictator game experiment by Kahneman et al. (1986) and Forsythe et al. (1994), we do find other factors called “context effects” that may influence such an experiment (Camerer & Thaler, 1995). However, behavioral theorist experiments did not consider external economic factors such as crises to be a possible cause for rational and selfish behavior. The current research aims to clarify this unidentified area.

Lastly, marketers have spent tremendous amounts of money and effort in researching and understanding consumer behavior (Hawkins, 2010). Consumer behavior research, in fact, was driven by marketeers to better serve consumer needs (Schiffman, 2012). With this research we

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aim to offer new insights that can help to better predict consumer behavior in times of crisis.

After all, the evolving discipline of behavioral economics can help businesses better defend against inaccuracy and waste (Harvard Business review, 2009). This paper aims to do that by expanding the research on how external economic factors effect consumer choice. This in turn can be applied in the field by marketers to better serve consumers and predict consumer behavior.

Theories related to the research question, together with the hypotheses, will be introduced in chapter 2. Chapter 3 focuses on the data and methods used in this research, followed by an overview of all statistical results in chapter 4. Subsequently the interpretation and significance of our findings are reviewed in the discussion section.

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2. Literature review

This chapter provides information gathered from existing literature related to the research question. Since this thesis will have a strong focus on contributing to the literature of behavioral theory and consumer behavior, it is essential to understand its main components. Therefore, this section will first of all clarify behavioral economic theory. We continue to introduce three hypotheses while discussing concepts related to behavioral economics, game theory, consumer behavior, crises, and possible correlations.

Behavioral economics

“It says something interesting about the field of economics that there is a sub-field called behavioral economics” (Mullainathan & Thaler, 2000).

Behavioral economics, like behavioral strategy, is very much concerned with the psychological aspect of human behavior. The same accounts for the relationship between economics and behavioral psychology, which is a science of human behavior (Hursh, 1984). Behavioral economics makes use of psychological experimentation to develop theories about human decision making. According to behavioral economics, people are not always self-interested, benefit maximizing and cost minimizing individuals whose preferences stay stable (BE guide, 2014).

The value of economic concepts in behavioral psychology is determined by their empirical validity when evaluated in a lab with individual subjects. Second, the usefulness of economic concepts in comparison to well-established behavioral ideas (Hursch, 1984). In practice the validity is measured as the accuracy of economic prediction with the results of behavioral experiments. The utility is evaluated as a noticeable difference between economic concepts and current behavioral principles (Hursch, 1984). That idea plays a key role in this paper as we will

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bring forward various examples and conduct experiments to test possible differences between economic predictions and experiment outcomes.

There are three crucial aspects in which humans differ from the standard economic model which are also defined as the “three bounds of human nature” (Mullainathan & Thaler, 2000).

These three traits are bounded rationality, bounded willpower and bounded selfishness. The bounded rationality term was suggested by Simon (1955) to offer a more realistic description of the capability that humans have in solving problems. Since humans only have a limited amount of time and brainpower, we should not expect that they can solve difficult problems optimally all the time (Mullainathan & Thaler, 2000). Bounded willpower highlights the reality that people make decisions that are not always in their best interests in the long term. This can be due to self-control reasons e.g., not having saved enough but continue spending too much.

Therefore, even though real humans might know what is best, they sometimes fail to choose it (Mullainathan & Thaler, 2000). That people are not as selfish as believed in economics, is captured in the term unbounded selfishness. Examples of selfless behaviors are also observed in laboratory experiments such as prisoner dilemma games, where subjects consistently collaborate. Even in ultimatum games they consistently reject unfair offers (Mullainathan &

Thaler, 2000).

The assumptions of economic theory and knowledge within psychology differ from each other quit a lot (Kahneman, 2003). Those assumptions or ‘beliefs’ consists of three ideas specifically (Thaler, 2016). First, people have rational preferences and unbiased beliefs and expectations. Furthermore, people make optimal choices based on these beliefs and preferences.

Third, the primary motivation of individuals is self-interest. In short, this description shows assumptions which include rational choices, perfect information, and profit maximization. It is these assumptions that define homo economicus (Thaler, 2016). Surely psychologists and other behavioral scientists began testing these assumptions which led to a stream of work that became

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increasingly critical about traditional economics. Conceptual, methodical and empirical work of Nobel prize winners Amos Tversky, Daniel Kahneman, Richard Thaler, Herbert Simon, George Akerlof, and Vernon Smith contributed towards understanding the behavioral dynamics of economic decisions (Barkovic, 2019). The goal of behavioral scientists is therefore clear:

“providing concrete evidence that will help develop economic theory” (Camerer & Thaler, 1995). This paper aims to contribute to this lofty goal.

Homo economicus

The homo economicus is self-interested, outcome-oriented and a rational actor (Gintis, 2000).

That standard model of the individual in economic theory might be accurate for specific market settings but are rather inaccurate outside this setting (Gintis, 2000). For instance, if people are indeed caring only about their own self-interest, we should not see people becoming addicted to harmful addictions. Think of the use of drugs, gambling and many other harmful habits. Also, we are all aware that people do show charitable behavior and thus help others outside themselves or family members. A research by a Dutch charity organization shows that in 2018 the Dutch have spent 3.1 billion euros to charities (GDN, 2018). Furthermore, we also know that people have a concern for fairness. In fact, people dislike misbehavior of one stranger to another stranger and would even be willing to punish this misbehavior at some costs of themselves, thus proving non-selfish behavior (Kahneman, 2003).

Nevertheless, economists consider these observations rather weak in argumentation and hold that homo economicus assumptions are in fact reality. There are several examples to clear this point. Drug addiction might seem a good example of people clearly making a choice that is not in their best self-interest. However, drug taking may be a risky behavior for which the net benefit is positive for most and negative for some (Gintis, 2000). Furthermore, most charitable giving is not anonymous. Self-interested agents might do charity because it will improve their

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reputation and consequently benefits them with their neighbors or colleagues. Thus, even if the act of charity seems selfless, it might ultimately be for the benefit of the agent because charitable behavior can lead to benefits for the giver (Anik, 2009).

Game theory

Game theory is the study of how interacting decisions of economic actors generate results that are related to the preferences (or utility) of those agents, even if none of the individuals intended those results (Ross, 2019). The importance of game theory in this research is that it serves as a foundation of the expectations for the games in our experiment. Briefly the goal of game theory is therefore to help understand how decision-makers interact (Askari et al., 2019).

A ‘game’ is defined as any circumstance in which at least one agent may only maximize his utility by predicting the responses to his actions by one or more other agents. The term

‘agents’ in this sense refers to all players participating in the game (Ross Don, 2019). Game theory aims to predict how players will behave in such scenarios and what will happen as a result. The idea has been used in a variety of fields including economics, other social sciences, biology, and computer science (Van Damme, 2015). It must be said that as with any concept in economics, the prediction about what people will do is based on the assumption of rationality (Camerer,2003). Game theory provides the starting point for the expected results of the games in this study.

One of the most famous examples of all games is the Prisoner’s Dilemma (Ross Don, 2019).

Professor Ross (2019) explains the dilemma as follows: The players in this game are told that the police have arrested two people from which they know that both have played a role in an armed robbery. But because of a lack of evidence the police cannot get a jury to convict.

However, they do have enough evidence to imprison both persons for two years each for auto theft. The police therefor make an offer to both prisoners. If you confess the robbery with the

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other person, and that person does not confess, you will go free and the other will get 10 years.

If you both confess, you will both get 5 years. If neither confesses, then you will get two years each for auto theft. Game theory can be applied to helps understand the best possible action to take. The first step is modeling the situation in terms of utility function. The numbers below are used to express each player’s ‘payoff’ in all outcomes. The strategic form of this game is displayed in a single matrix as seen in Figure 1.

Go free: 4 2 years: 3 5 years: 1 10 years: 0

Figure 1. Strategic form of the Prisoner’s Dilemma (Don Ross, 2019).

The matrix consists of four cells which represent each combination of actions for every player in this game. The first number is the payoff for Player I and the second number is the payoff for Player II. Now each player may decide to either confess or refuse. But the decision, according to game theory, should be based on the outcome with the highest payoff. In case Player II confesses, Player I receives a payoff of 2 for confessing and 0 for refusing. If Player II rejects, Player I receives a payoff of 4 for confessing and 3 for refusing. As a result, regardless of what Player II does, Player I is better off confessing. Meanwhile, Player II assesses her activities by comparing her payoffs down each row, and she reaches the same conclusion as Player I.

The dictator game and ultimatum game are also well-known experiments in the field of behavioral economics. Kahneman et al. (1986) introduced the dictator game as an experiment to show whether people behave like rational beings that maximize their utility, a typical

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description of homo economicus. One player (the proposer) is endowed with a sum of money and can choose how much to share with the other player (the responder). This can range from zero to a substantial amount of the endowment. Contrary to neoclassical economic believe, human populations have been found to be more generous than homo economicus, and as a result, the majority of people rarely offer nothing to the recipients (Camerer, 2003). The ultimatum game has a similar setting as the dictator game. The only difference is that the responder can either accept or reject offers from the proposer, risking that both players will receive nothing in the end (Camerer & Thaler, 1995).

Consumer behavior

“As individuals we are all unique. However, one of the most important constants among all of us despite our difference is that, above all, we are consumers” (Schiffman et al., 2012).

Schiffman, Kanuk and Hansen (2012) have defined and explained the concept of consumer behavior and its attributes in their textbook in detail. The term consumer behavior describes two different types of consumers: the personal consumer and the organizational consumer. The personal consumer purchases goods and service for their personal use. This can be products for a person’s household of services for their home. The second category, organizational consumer, includes companies, governments, agencies, institutions, and all other examples that refer to use in order to run the organization. This research is merely concerned with the first category personal consumers who makes choices for their personal use or household use. This will also be reflected in the final experiment.

The need to research consumer behavior is rooted in marketing and has evolved in the late 1950s. Marketers began to understand the importance of consumer behavior exploration as a way to research what consumers really wanted. Similar to behavioral economics, the field of consumer behavior also borrows concepts from other theories that are found in psychology and

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economics. In fact, early theories of consumer behavior were based on economic theory, which as explained earlier, assumes that people act rational and are maximizing their benefit. Later research revealed that consumers are not only likely to be influenced by their family or friends but also by mood, situation, and emotion (Schiffman, 2012). These so-called situational factors are discussed more in detail later. When combining the main factors influencing consumers, we can form a model of consumer behavior as displayed in Figure 2.

Figure 2. A simple model of consumer decision-making (Schiffman et al., 2012).

The process of consumer decision-making can be viewed as three different stages: the input stage, the process stage and the output stage. These stages are found in the simplified model of consumer decision-making in Figure 2. The input stage influences the consumer’s need for a

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certain product or service and consists of two components which can be described as major information sources. These information sources influence the consumer’s recognition for a need. This happens through the firm’s marketing efforts (the product itself, its price, promotion and place) and sociocultural environment (such as the person’s family, social class and culture).

The combination of these influences is likely to affect what the consumer is going to buy and how the consumer is going to use it (Schifmann et al., 2012).

The process stage explains how the consumer makes the decision. Based on the model we can see that the psychological field of the individual (motivation, perception, learning, personality and attitudes) affect how the external factors from the input stage influence the recognition of the need, pre-purchase search for information and evaluation of alternatives. The latter, in turn, is memorized as an experience which influences the existing psychological field.

The output stage of the consumer decision making process two post-decision behaviors.

These activities are also closely related and are named purchase behavior and post-purchase evaluation. The purchase behavior shows two elements which do differ from each other. The

‘trial’ purchase means that the consumers evaluate the product through direct use. If the consumer is satisfied there will be a repeat purchase in the future. What this theory shows is that every individual is a consumer, and every consumer makes decisions through a process that is influenced by external and internal factors. This supports the idea that we may expect different behavior in our research depending on external influences.

Consumer choice in behavioral economics

Consumers are continually making choices among products. But at the same time, consumers lack full information about prices of goods. Their information about the quality variation of products is even less accurate because this information is harder to obtain (Nelson, 1970). A foundation of consumer choice is that it requires alternatives. If there are no alternatives to

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choose from, there is no decision making and there are several models to describe this process (Barkovic, 2019). One of the benefits of the neoclassic economic assumptions is that it helps to understand choices that individuals make. But completely depending on this normative theory of economists will lead to systematic errors in describing or forecasting consumer choice (Thaler, 1979).

A more realistic model to describe or predict consumer behavior can be achieved by using the prospect theory (Kahneman & Tversky, 1979). This concept is introduced as a critique on expected utility theory being a descriptive model for decision making (Bernoulli, 1738). It is a defined as a descriptive model of risky choice in which the carriers of utility are not states of wealth but gains and losses relative to a neutral reference point (Kahneman, 2003). We can first look at the following example to illustrate the difference between utility and prospect theory:

Two persons get their monthly report from a broker:

A is told that her wealth went from 4M to 3M;

B is told that her wealth went from 1M to 1.1M.

Question 1: Which of the two individuals has more reason to be satisfied with her financial situation?

Question 2: Who is happier today?

According expected-utility theory you should only be concerned with question 1 because that holds relevance since only long-term consequences matter. Therefore, the expected-utility theory does not count short-term emotions associated with gains and losses. However, this is psychologically unrealistic (Kahneman and Tversky, 1979). The results of existing research led to the several important outcomes. First, gains are treated differently than losses. In case of potential gains, people tend to be rather risk averse. Whereas for losses, people tend to be risk seeking. The second finding is that outcomes received with certainty are overweighted to uncertain outcomes. Lastly, the structure of the problem or question may affect what option the subjects chooses (Kahneman and Tversky, 1979).

The endowment effect can also be used to help explain consumer behavior. Loss-aversion holds that the response to losses is much more intense than the response to gains (Kahneman,

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2003). In other words, pain is a more powerful sensation than pleasure. This helps to understand the endowment effect: people generally will demand more to sell an item they own than they would be willing to pay to acquire the same item (Thaler, 1980). The same type of behavior is observed during crisis as it significantly effects risk aversion (Ang, 2001).

Situational effects on consumer behavior

It is known that situational variables can influence consumer behavior and these variables can substantially enhance the ability to explain and understand this behavior (Belk, 1975). In fact,

“situational variables may account for more variance than actor-related variables” (Belk 1975).

A study by Smith et al. (2005) confirms this by stating that consumer choices are strongly affected by the environment. Nevertheless, both individual and situational factors should be investigated to explain consumer choice (Engel et al., 1969). A situation can be defined as a point in time and place. More specifically, situations are short encounters with parts of the whole environment that an individual has access to at any one moment (Belk, 1975). Individual features would include personality, intellect, gender and race which all stay stable over times and place.

Features of consumer situations exist of five groups (Belk, 1975). Firstly, the physical surroundings which include features such as the geographical location, decor, weather or other material surrounding. Second, the Social Surroundings offer more depth to the description of a situation and therefor includes other persons present that are present and their characteristics and roles. Thirdly, the Temporal Perspective is a type of situation that is specified in units such as time of the day or season of the year. This can be used in analyzing differences in behavior from or towards a specified situation of time. Fourth, the Task Definition of a situation include an intent or requirement to choose or obtain information about a certain purchase. The task can reflect different roles anticipated by the individual. For example, the task to find birthday gifts when shopping in the mall, is different from a situation of someone shopping in the mall for a

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small purchase or personal use. Fifth, Antecedent States are the final group of features which characterize a situation. These consist of momentary moods and momentary conditions.

Momentary moods may include pleasantness, anger or for example acute anxiety. Momentary conditions cover things such as cash on hand, fatigue and illness. The example given by Belk (1975) to explain this phenomenon is a person that chooses a certain movie when feeling depressed, in order to feel happier.

We learn from this that situational factors, outside personal traits, indeed influence consumer behavior. We should therefor consider that a situation that causes a feeling of uncertainty and anxiety may directly affect the choices a person makes. This leads us to clarify if situational factors such as an economic crisis, could potentially influence consumer choice.

After thoroughly investigating the concept of consumer behavior in the past paragraphs, we argue that individual choices in our experiment can change, solely based on the difference of the situation. Therefor we hypothesize that:

Hypothesis 1. A situation of economic crisis will influence consumer choice.

The following conceptual model shows the relationships that is studied:

Crisis Economic crisis Consumer choice

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Crisis

Originally the term “crisis” comes from the Greek word kpinei, meaning “decision” (Starn, 1971). Crisis in general can be defined as a serious threat which requires making critical decisions under time pressure and highly uncertain circumstances (Rosenthal, 2001). Crises can be characterized by a high degree of uncertainty followed by a disturbance of regularities. Often such a situation involves acting quickly under time pressure in order to avert the threat.

(Rosenthal, 2001). There are three stages in crisis: pre-crisis, crisis event and post-crisis (Coombs, 2015). During the pre-crisis individuals should be concerned with preparing for crisis. In a business setting this would include crisis management team formation and crisis planning and organisation. In the second stage, during the crisis event, crisis recognition and prevention from the crisis damage are most crucial. In the post-crisis stage the main focus lies on determining the damage caused by crisis, followed by recovering from the crisis and lastly preparing for the next possible crisis (Jahantigh et al., 2018).

Nowadays however, we use this term in everyday experience, politics and it mainly has become a central concept because of the term: economic crisis (Koselleck, 2006). Related to the research question we are mainly concerned with the latter. An economic or financial crisis is the result of multidimensional events which lead to large-scale balance sheet problems of households, firms and even governments (Claessens, 2014). We also tend to see declines in real estate prices and an increase in unemployment (Stiglitz, 2009). There is a fairly large number of existing literatures to be found that is primarily concerned with the causes of financial crisis (Blankenburg, 2009) and how to prevent or cope with such crises on a global scale (Dullien, 2010). Interestingly, financial crisis sometimes appears to be caused by “irrational” factors such as spillovers among financial markets and runs on banks (Claessens, 2014). Nevertheless, contributions on the effect of crisis as an independent variable on the rational and self-centered

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behavior of consumers specifically seems inadequate. Therefor this research aims to contribute to that topic.

Crisis effects on consumer behavior

The concept of consumer behavior is an important matter in economics and marketeers have spent hundreds of millions of dollars to understand and study consumer behavior (Hawkins, 2010). Consumer behavior is defined as a process in which individuals purchase or make use of products and services to satisfy their needs (Mansoor, 2011; Perner, 2008).

We do find results with regards to the effect of crisis on consumer (buying) behavior in general. Also, it is widely known that consumer behavior can be influenced by several factors including psychological, social, cultural, economic, and personal factors (Ramya, 2016). This research is mainly concerned with the effect of a crisis on consumer behavior as an economic factor. Earlier studies so far already found that consumers tend to decrease their spending, prefer low priced products, and focus on saving during an economic crisis (Filip, 2011). This idea explains why we see an extreme decline in GDP during the Covid-crisis in the Netherlands (CBS, 2020).

It is less straightforward to find whether a crisis specifically triggers rational and self- interested behavior. Many people experienced selfish behavior during the start of Covid crisis as consumers excessively plundered shelves in supermarkets and start hoarding, leaving other people with less food and other necessities. Causes for such behavior can be found in worry of consumers with regards to their finances and resource availability (VanDyke, 2020). It is not unusual that uncertainty coupled with fear of shortages instigate such behavior (Dasgupta, 2020) or that self-interest overpowers social interest during crisis (Higgens, 2013). As for rationality however, a study conducted in 2020 that tried to find a correlation between stress

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and rationality showed that stressful circumstances do not reduce or increase the participants’

ability to make rational economic choices (Cettolin, 2020).

Rationality

Rationality is one of the fundamental pillars of Economics (Cettolin, 2020). A rational player should be able to fulfill several actions. First of all, analyze outcomes by ranking them according to their contributions to his well-being. Second, identify which order of choices are connected with which outcome. Third, given the behaviors of the other players, choose actions from a range of options that provide the best outcomes (Don ross, 2019). In summary, an individual is defined as an economically rational agent if it has options and chooses among them in a way that appears to be the best for its objectives.

The assumption of traditional classic economic theory tells us that individuals are behaving in a rational way and make rational decisions. On the other hand, when people make choices and decisions that go against the assumption of rational utility-maximizing behavior, we consider these choices to be irrational (Bankovic, 2019). Furthermore, the idea that humans always act rational is challenged by the same concept of risk aversion (Kahneman & Tversky, 1979). Though economists stay rather defensive and behavioral economic theorists continue to be overwhelming critical about the assumptions that humans are fully rational. These assumptions of rationality are said to be an approximation, which is made in the belief that people are rational when the stakes are high (Kahneman, 2003). Starting from this idea we can test the concept of rational decision making. We test if a situation of high risk and high stakes, affects rational behavior. Crises are a typical example of an external factor that carries high risks (Dasgupta, 2020) and therefore, we hypothesize that:

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Hypothesis 2. An economic crisis is positively related to rational choice.

The following conceptual model shows the relationships that is studied:

Self-interest

A homo economicus always decides to start from its own profit and decides on the possibility of having the highest net benefit (Bankovic, 2019). According to many influential theories of human behavior, the self-interest motive is especially powerful. After all, the first principle of economics is that every agent is motivated by self-interest (Edgeworth, 1881). However, even Edgeworth himself wat quite aware that this principle of economics is not particularly realistic (Sen, 1977). The reason is that one can define a person’s interest in such a way that it does not matter what choices he makes; it can be seen as an act to fulfill his own interest. This is also true in the explanation provided earlier in this paper by Gintis (2000) about the use of harmful habits and charitable behavior. Even though it is proven that acts of charity indeed serve psychological aspects of the self, it can in essence not be considered to satisfy the logic of most rational choice models. The reason is that the agents “feeling good” after contributing to a public good, is of no material consequence to them and should therefore not be considered self- interested behavior according to the definition of the assumption (Miller, 2001). More importantly, the empirical results of an experiment called the “ultimatum game” differed dramatically from the predictions of game theory, which assumes self-interest (Camerer &

Thaler, 1995). The dictator game experiment shows similar results. In the dictator game, the first player is handed money and makes a decision regarding the split of the pie with the second player who must accept the result. According to traditional economics, if a player is an income maximizer, then the person should offer nothing or the smallest unit available. Nevertheless,

Economic crisis Rational

decision-making

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results of Kahneman et al. (1986) reveals that three-quarter of students opted for the equal split (List, 2007). But since self-interest overpowers social interest during crisis (Higgens, 2013), we could argue that a crisis can foster selfish behavior. Furthermore, consumers show hoarding behavior if they worry about their finances or resource availability (VanDyke, 2020). Since this behavior can be categorized as self-interested, we will test whether people indeed act self- interested in our experiment. Therefore, the following hypothesis is presented:

Hypothesis 3. An economic crisis is positively related to self-interested behavior.

The following conceptual model shows the relationships that is studied:

Economic crisis Self-interested

behavior

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3. Data and Methods

The essential purpose of this paper is to provide concrete evidence that will help develop economic theory. Through an experimental design we aim to establish a cause-and-effect relationship between economic crisis and consumer choice with regards to rationality and self- interest.

Sample

This paper carries out two forms of research: primary research and secondary research. We do this by conducting the experiment ourselves to gain new insights, but also through using pre- existing data to compare the results of both. Since primary data is needed to research possible correlations, a sampling method and criteria is selected. Through existing studies we can make several assumptions about the choices made by different types of people. For example, women tend to be slightly more generous to split the money received during the dictator than men (Eckel & Grossman 1998). Furthermore, the experiment by Bekkers (2007) based on the dictator game showed that donations increase with age, education and income. Thus, according to secondary research, different outcomes might occur dependent on gender, age and education.

As a result, these factors are considered during the data collection by distributing the survey across people that differ in these characteristics.

Furthermore, to strengthen the internal validity of this research we do not limit the samples to students only as in the case of Kahneman, Knetsch and Thaler (1986). Instead, the population of this study consist of adults living in the Netherlands between 20 and 55+ years old. Groups are divided by age, gender and degree to find possible differences in characteristics. The sample size of this experimental survey consists of 115 respondents. That is more than the number of subjects used in an earlier dictator game experiment by Eckel & Grossman (1996) and statistically considered sufficient for this research.

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Data collection

A quantitative research helps to test the formulated hypothesis and offer clear results by collecting numerical data that are analyzed using mathematically based methods (Sukamolson, 2007). This research provides quantitative data to formulate relationships. The data is gathered by using (online) surveys, as survey research is proven to be successfully used for similar studies (Kahneman & Tversky, 1986) and a known research method in many other behavioral strategy papers (Powell, 2011). Furthermore, the use of surveys allows to study a relatively large population compared to qualitative methods such as interviews. Finally, the use of quantitative data through surveys will help to easily compare results with earlier experiments such as from Kahneman & Tversky (1986), Eckel & Grossman (1996) and Bekkers (2007) and more. The data is gathered through a survey program and distributed online only because current Covid-restrictions limit other methods. In order to reach a sufficient amount of respondents, social media platforms are used to share the survey. The sruvey software is called Qualtrics and offers important features. Since all survey responses are done on distance (without the researcher present), we want to avoid double entries. Through automatically tracking IP addresses in the survey software, we disable double-entries by a person that has already answered the survey.

After collecting all data within a time period of several weeks, 115 individuals completed the experimental survey. Answers of the (14) individuals that did not completely finalize the survey are not considered in the data analysis. The gender split was equally distributed with approximately 50% of the respondents being male and 50% female. The distribution with regards to age group and level of education however are not as equally distributed. We observed a vast majority of respondents being in the 20-30 years category and another majority can be found in the bachelor’s and master’s category.

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Statistical Analysis

Through the output of the Qualtrics survey software we can easily interpret the absolute or percentual results for each answer given. Additionally, the statistical software SPSS is used to analyze all gathered data and measure the statistical significance our findings. There are two statistical tests used for the latter.

First of all, we try to investigate whether there are significant changes in the choices made by respondents before a crisis and during a crisis. This means there are two measure moments “no crisis” and “crisis”. Furthermore, the experimental survey is answered by the same group of people because both measure moments are considered in the same single survey.

Based on that, a paired sample t-test is used. This is a statistical procedure to measure the mean difference between two sets of observations. It is used to subject the same group to two conditions and then to compare these two scores. The two sets of observations in this analysis are time (no crisis, crisis) which is the independent variable, and the subjects are all individuals that answered the survey. The dependent variables are rationality and self-interest.

A different statistical analysis is applied to measure the difference between the individual’s characteristics. The characteristics that are collected in the analysis were age, gender and level of education. Based on the data we know that age and education are not normally distributed.

We try to test whether our sample indeed shows (significant) differences in answers based on gender as suggested in earlier research by Bekkers (2007). To test this, a mixed ANOVA analysis is used. In the Mixed ANOVA there are two types of independent variables in the design: at least one between-subject variable and at least one within-subject variable. The within-subject variable is “time” (no crisis, crisis) and the between-subject variable is gender (man, woman). The main goal of this mixed ANOVA is to determine if the within-subjects and between-subjects factors interact on the dependent variable. The dependent variables stay rationality and self-interest.

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Experiment design

In an experiment participants are allocated to at least two experimental conditions at random.

Randomization and treatment take place within one survey questionnaire in case of a survey experiment. The survey experiment in this research covers elements from both the ultimatum game and dictator game. The survey consists of three experiments in two scenarios. One which frames a normal situation and another part which frames a crisis situation. In the first scenario respondents are asked to imagine that they are in a normal economic situation with a stable job and income, and they are requested to make decisions from this perspective.

To begin with, the dictator game is implemented as brought forward by Kahneman et al.

(1986) in the first experiment. The respondent is ‘placed in room A’ and the other participant is ‘placed in room B’. They cannot see or communicate with each other. Solely the person in room A, the respondent, decides how the money is split and the person in room B must accept.

Guth (1990) proposed that one should try to find out whether the result is still valid when the stakes are higher. Also, it is believed that people are rational when the stakes are higher (Kahneman, 2003). Therefore, with every other question the stakes are increased. We use the following formula to increase the stakes in three steps. In the first step the questions relate to an amount of X euro’s. In the second question the stakes are increased to (X euro’s * 2) and lastly (X euro’s * 5). Consequently, a series of the following type of questions is asked:

“You are given an X amount. You are then asked to decide how much of this money you want to share with the person in room B. This person must accept your offer. What amount will you give the person in room B?”

In the second experiment, similar to the ultimatum game introduced by Guth et al. (1982), the survey tells that this experiment includes two persons, both the respondent and someone they do not know. The respondent is ‘placed in room A’ and the other participant is ‘placed in room

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B’. They cannot see or communicate with each other. Underneath we can find an example of the questions related to the ultimatum game:

“You are given an X amount. You are then asked to decide how much of this money you want to share with the person in room B. If the other person does not accept your offer, you both get 0 euros.”

In the last experiment the roles change, and we introduce what we call the ‘reversed ultimatum game’ in the third experiment. In this game the respondent is asked which offer they would minimally accept to receive from the person in the other room. These questions look as follows:

“The other person in Room B receives X euros. He is asked how much money will be shared with you. If you do not accept his offer, you both get 0 euros. What amount would you minimally accept?”

In the second scenario we ask the same questions again according to the three experiments.

However, in this part of the survey a different situation is given to the respondent. We do this based on the characteristics of an economic crisis which include high uncertainty and an increase in unemployment (Rosenthal, 2001; Stiglitz, 2019). Therefore, the survey asks the respondent to imagine living in a scenario that they lost their job during an economic crisis and that it is uncertain when this crisis will be over. The description is stated below:

Please note that the economic situation has now changed. Imagine yourself in the middle of an economic crisis. Many people, including you, have lost their jobs. It is uncertain when the economic situation will improve. Please answer the following questions from that perspective.

What follows are the same three experiments: dictator game, ultimatum game and reversed ultimatum game. The goal is to test whether the answers change dependent on the time or

‘crisis’ variable. Based on the results of the respondents and existing literature we will conclude

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whether those choices are in line with traditional economic theory, and thus rational and self- interested, or not.

Reliability concerns

Currently in ultimatum game research, enough independent studies have been carried out to be confident that the basic phenomena are robust (Camerer & Thaler, 1995). The closely related

“dictator game” however is far more sensitive to design issues. Therefore we should consider a few effects in order to insure the reliability of the experiment (Camerer & Thaler, 1995). First,

“social distance” can be manipulated through the context in which the experiment is set.

Additionally, whether the subjects in the experiment receive their money in an envelope and in what way, can already impact the results. Also, if the subjects are assured that the experimenter cannot observe each action, this also may influence their decision-making. A combination of these factors can grow the social distance between the allocator and recipient which leads to lower offers (Camerer & Thaler, 1995).

In the experiment conducted during this study, we will not be handing subjects real money.

Furthermore, at the beginning of the survey, each subject is reminded that all answers are completely anonymous. Lastly, the subjects are not requested to ‘sell’ anything to the recipient, but rather to chose if and how much money they want to give away to a stranger they will not meet. The aim is to create enough social distance; however, certain limitations will be reviewed when discussing results.

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4. Results

Expectations

Based on our hypothesis we measured two dependent variables: rational choice and self- interested behavior. To test the hypotheses, we examined how both rational decision making and self-interest can be measured by using similar experiments presented in prior research. We use the outcome of previous papers to compare results of our experiment to those expectations.

These experiments have gained attention because the empirical results differed dramatically from the predictions of game theory, which assumes self-interest (Camerer & Thaler, 1995).

Based on the findings of Kahneman et al. (1986) we should expect to see the majority of respondents to equally split their endowment in the ultimatum game in a normal economic situation. Furthermore, research by Bekkers (2007) based on the dictator game showed that donations increase with age and educational level. These factors are also taken into account in this studies’ data analysis. Additionally, in the dictator game the mean amount donated is 20%

of the endowment when studying research by Camerer (2003).

These choices clearly go against traditional economic theory. Therefore, we study whether the results differ in a crisis situation. In case of an increase in self-interested behavior we should see an increase in respondents to keep their entire endowment to themselves (Bekkers, 2007).

Furthermore, with regards to rationality, when the respondent is asked which amount they would minimally accept in the reversed ultimatum game, they should accept the least monetary offer. After all, a typical econ would always decide the possibility of having the highest net benefit and therefor avoid receiving nothing (Bankovic, 2019). Furthermore, subjects in ultimatum games tend to avoid ‘unfair’ offers and offer a fair split. This charitable behavior is considered as selfless by behavioral economists (Mullainathan & Thaler, 2000).

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Survey results

In this section the survey results are revealed. The survey experiment has been completed by 115 individuals ranging from 20-55+ years old who are living in the Netherlands. The sample consists of people differing not only in age, but also gender and level of education. The gender split is equal with approximately 50% of the 115 respondents being man and 50% woman. We have taken in account the characteristics gender, age and education in our statistical analysis which will follow later in this results section. Table 1 displays the number of our sample based on each characteristic. In the following sub-sections we will discuss the results of our survey, followed by a statistical analysis to test the significance of our findings.

Age Education Gender

20-30 years 77 MBO 17 Man 57

30-40 years 26 Bachelor 56 Woman 58

40-55 years 10 Master 41

55+ 2 Doctorate 1

Total 115 Total 115 Total 115

Table 1. Sample

Dictator game results

In Figure 3 we find the results of the first question related to the dictator game. The respondents were asked how much money they would share with the person in room B who they do not know and cannot see or communicate with. Following the rules of a typical dictator game, the other person must accept any offer received. We notice that the results of this experiment are in line with statements by Camerer (2003), arguing that in the dictator game the mean amount donated is 20% of the endowment. In these results the mean lies between 20% and 25% of the endowment. We also test whether these results change when the stakes are increased from 100

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euro’s to 500 euro’s. Figure 4 shows that the mean amount donated stays approximately 20%

of the endowment. All in all, our dictator game results reveal that the majority of the respondents (almost 55%) chose to share at least 20% of their endowment with a stranger that they cannot see and will not meet. This result is consistent with earlier dictator game experiments.

Figure 3. Dictator game results before crisis with a 100 euros stake

Figure 4. Dictator game results before crisis with a 500 euros stake

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As explained, dictator game experiment is done in two scenarios. The results in Figure 3 and 4 display the results in a normal setting before an economic crisis. The results of the dictator game experiment ‘during crisis’ are displayed in Figure 5. We read that the mean stays between 20%

and 30% of the endowment. A similar mean result is displayed when the stakes are increased from 100 euros to 500 euros as seen in Figure 6. The absolute percentages however do slightly change compared to the dictator game in our first (no crisis) scenario. These results tell that during the crisis scenario, the percentage of people that give away any amount to a stranger increase to 60% in case of a 100euro’s stake and even 65% when there is a 500 euros stake.

Figure 5. Dictator game results during crisis with a 100 euros stake

Figure 6. Dictator game results during crisis with a 500 euros stake

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Ultimatum game results

The ultimatum game has a similar setting as the dictator game in the experiment. However, the respondents are told that the rules are slightly different and that the stranger can either accept or reject their offer. In case of a rejection, both the respondent and the stranger will get 0 euros.

The results of our survey are consistent with the findings of Kahneman et al. (1986) who states that the majority of respondents equally split their endowment in the ultimatum game. Figure 7 clearly displays that over 60% of the respondents in our ultimatum game experiment split half of their endowment with a stranger. When the stakes are increased, we notice a slight decline in the amount of people to offer at least half of their endowment as seen in Figure 8. Looking at the ultimatum game results ‘during crisis’ in Figure 9 and Figure 10 we again notice that also the mean amount offered by the subject to the stranger declines as the stakes increase.

Figure 7. Ultimatum game results before crisis with a 100 euros stake

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Figure 8. Ultimatum game results before crisis with a 500 euros stake

Figure 9. Ultimatum game results during crisis with a 100 euros stake

Figure 10. Ultimatum game results during crisis with a 500 euros stake

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Reversed ultimatum game results

The difference between what is called the ‘reversed ultimatum game’ and the original ultimatum game can be found in its name. The roles of subject and stranger are reversed, making it possible for the subject to either accept or reject an offer. According to previous results, the majority in the ultimatum game tends to split the amount equally. However, in the reversed ultimatum game most respondents accepts less than half of the endowment as a sufficient offer.

This corresponds with the results discussed in Güth & Teitz (1990) and Camerer & Thaler (1995), where respondents frequently reject offers below 30% (Gintis, 2000). When the stakes are increased, we see that the outcomes stay almost the same in Figure 11 and 12. The same accounts for the choices during crisis, see Figure 13 and 14, which both show similar results as the ones before crisis.

Figure 11. Reversed ultimatum game results before crisis with a 100 euros stake

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Figure 12. Reversed ultimatum game results before crisis with a 100 euros stake

Figure 13. Reversed ultimatum game results during crisis with a 100 euros stake

Figure 14. Reversed ultimatum game results during crisis with a 500 euros stake

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Statistical analysis

Based on the survey results we observed differences between the decisions of our subject before and after crisis. Through a statistical analysis we can test whether these differences between choices made before and after crisis are significant. Below you can find three tables which correspond to each of our three experiments: dictator game, ultimatum game and reversed ultimatum game. Since we are specifically interested in analyzing differences in time, we have paired each set of questions before crisis (e.g., Q1-Q3) to a set of question after crisis (e.g., Q1b-Q3b). Looking at the p-value of the set of questions referring to the dictator game experiments in Table 2, one can see that its p-value is smaller than 0.05. The same accounts for both the ultimatum game results in Table 3 and reversed ultimatum game results in Table 4, which also indicate p<0.05.

Table 2. Statistical significance difference dictator game results

Table 3. Statistical significance difference ultimatum game results

Table 4. Statistical significance difference reversed ultimatum game results

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It is also interesting to find out whether there are any significant variations in gender-based responses in the sample, next to age and education. We perform a mixed ANOVA analysis to see if this is true. Other than results from Havens et al. (2006) show us, we cannot say that age or education have any significant effect on the amount given away in our experiment. We can also find in Table 5 that p<0.05 in case of gender. Therefore, these findings are in line with Bekkers (2007) who states that in the analysis of the amount donated, females and males do not differ significantly.

Table 4. Statistical significance difference based on characteristics (Q19= gender, Q20= age, Q21= education)

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5. Discussion

We can draw several conclusions based on the survey results and statistical analysis.

The dictator game results show that a majority of people will share at least 20% of their endowment with a stranger who they will not meet. This result is in line with prior research which reveals that the mean amount donated is 20% during a dictator game experiment (Camerer, 2003). In case of a dictator game, the self-interested choice is to keep the entire endowment to oneself (Bekkers, 2007). But in the second scenario, which depicts a crisis situation, we observed that the mean amount donated stays relatively equal. The statistical analysis confirms that there is no significant effect of a crisis on the choices made during the dictator game. However, we do notice that during crisis there is a slight increase of 10% that donates at least a minimum amount of money to a stranger.

Findings of the ultimatum game also confirm previous papers regarding this matter. Similar to Kahneman et al. (1986), this research proves that the majority of respondents offer 50% of their endowment to a stranger in an ultimatum game. Furthermore, as indicated before by Camerer and Thaler (1995), offers in our dictator game are lower than in ultimatum game too and in most cases still positive. In the reversed ultimatum game we found that most people accept at least 30% of the endowment as a satisfactory offer. These conclusions were in line with statements from Güth & Teitz, (1990) and Camerer & Thaler (1995), proving that respondents frequently reject offers below 30%. The rational choice is to accept any offer with a monetary benefit. This is because a typical homo economist would always choose the option with a net gain in order to avoid obtaining nothing (Bankovic, 2019). Furthermore, Kahneman (2003) stated that that there is a belief (or hope) that rationality is triggered when the stakes are high by some economists. Nevertheless, based on results of the survey experiment we can confirm that there are no significant changes in consumer choice, rational behavior or self- interested behavior. As a result, we should correspondingly reject hypothesis 1, hypothesis 2

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and hypothesis 3. Overall, this research confirms assumptions of behavioral economic theory based on experimental research outcomes, proving that people indeed tend to act irrational and make self-less decisions, even when stakes are increased, and a crisis exists.

Although the results of this paper are based on statistical outcomes, one is always concerned with certain limitations of a research. The same accounts for this paper. A survey experiment has various practical advantages, especially when making use of dictator and ultimatum game experiments. Nevertheless, we cannot unquestionably confirm that individuals would show similar behavior when there is real money in play. Also, there is some critique as to using such game experiments to measure rationality and self-interest. The setting in these games is normally not to be found in real-world practice. Furthermore, most of our findings confirmed prior research, with exception of the age and education effect on donation. Since the age groups and level of education of this research were not as equally distributed as gender, we are hesitant with the significance of the results related to that matter. Moreover, the survey frames a typical crisis, but it is unclear to what extent this situation is considered and treated like a real crisis by each respondent. Therefore, future experiments ought to reassure that the crisis variable is truly apparent for each respondent. Additionally, future research might be concerned with finding out whether these results are still valid when subject can lose real money, or through introducing a more realistic experiment to check for rationality and self-interested behavior apart from dictator and ultimatum games.

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6. Conclusion

Whereas neoclassical economic theory assumes rationality and self-interest in all people, there is a disagreement from the side of behavioral research. Nonetheless, contributions to the impact of anything as severe as a crisis on consumers' rational and self-interested conduct appear to be limited. One of the main goals of this research was therefore to contribute to behavioral research and thus help develop economic theory by asking to what extent a crisis influences people to act more self-interested and rational in terms of consumer decision making. An experimental survey was conducted consisting of three experiments. These are the dictator game, ultimatum game and reversed ultimatum game. These experiments were completed by 115 Dutch respondents in total. The majority of our findings are consistent with previous dictator and ultimatum game experiments. Even though we know that external and internal factors influence consumer choice, we found no evidence in our experiment that a crisis has a substantial impact on rationality and self-interest in terms of decision-making.

This paper started with a quote from Nobel prize winner Kahneman (2003), stating that “no one seriously believed that all people have rational beliefs and make rational decisions all the time”. We conclude our study by arguing that no one should think that all humans have rational ideas and always make rational decisions, because this is frequently untrue.

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7. References

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Anik, L., Aknin, L. B., Norton, M. I., & Dunn, E. W. (2009). Feeling good about giving:

The benefits (and costs) of self-interested charitable behavior. Harvard Business School Marketing Unit Working Paper, (10-012).

Askari, G., Gordji, M. E., & Park, C. (2019). The behavioral model and game theory.

Palgrave Communications, 5(1), 1-8.

Ariely, D. (2009). The end of rational economics. Harvard business review, 87(7-8), 78-84.

Barković, D., & Tuševski, B. Rational Decision Versus Irrational Decision.

Interdisciplinary Management Research XV, 15, 402-418.

Belk, R. W. (1975). Situational variables and consumer behavior. Journal of Consumer research, 2(3), 157-164.

Bernoulli, D. (1738). Hydrodynamica: sive de viribus et motibus fluidorum commentarii.

Blankenburg, S., & Palma, J. G. (2009). Introduction: the global financial crisis.

Cambridge Journal of Economics, 33(4), 531-538.

Camerer, C. F. (2003). Behavioral game theory: Plausible formal models that predict accurately. Behavioral and Brain Sciences, 26(2), 157-158.

Camerer, C. F., & Thaler, R. H. (1995). Anomalies: Ultimatums, dictators and manners.

Journal of Economic perspectives, 9(2), 209-219.

CBS, (2020). Drugsgebruik, 12 jaar of ouder. Leefstijl en preventief gezondheidsonderzoek; persoonskenmerken.

CBS, (2020). Wat zijn de economische gevolgen van corona? [Online] Available:

https://www.cbs.nl/nl-nl/dossier/cbs-cijfers-coronacrisis/wat-zijn-de-economische-gevolgen- van-corona-

Cettolin, E., Dalton, P. S., Kop, W. J., & Zhang, W. (2019). Cortisol meets GARP: the effect of stress on economic rationality. Experimental Economics, 1-21.

Claessens, M. S., & Kose, M. A. (2013). Financial crises explanations, types, and implications.

Claessens, M. S., Kose, M. A., Laeven, M. L., & Valencia, M. F. (2014). Financial crises: Causes, consequences, and policy responses. International Monetary Fund.

Coombs, W. T. (2015). The value of communication during a crisis: Insights from strategic communication research. Business horizons, 58(2), 141-148.

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