Weimin Toh

Weimin Toh is an independent scholar. His main research areas are social semiotics, multimodal discourse analysis/multimodality, game studies, narratology and game-based learning. He is also interested in game design issues and user/player experience research. He is the author of A Multimodal Approach to Video Games and the Player Experience, which is part of the series of books published in the Routledge Studies in Multimodality.

Contact information:
weimin_c38 at hotmail.com


a0019282 at u.nus.edu

The Economics of Decision-Making in Video Games

by Weimin Toh


Decision-making is an important life skill. Video games can be leveraged to develop decision-making skills because they possess features such as multilinearity that require players to choose from among multiple options, and immediate feedback is provided to help players understand the outcomes of their choices. In the first part of this paper, we used a theoretical thematic analysis approach to code the players’ decision-making in video games using economics concepts, including return on investment and gratification, sunk gain/cost, loss aversion, scarcity, cost-benefit analysis and emotions and economic decision-making. In the second part of this paper, we addressed the game studies field more directly by relating the economic considerations to other factors within gameplay activity such as different game types, player types and the significance of emotional attachment to characters.

Keywords: video games, economic concepts, decision-making, loss aversion, scarcity, cost-benefit analysis



Decision-making is an important life skill. People make decisions to prioritize limited resources, such as time, and to consider how much effort is required to obtain desired returns. Organizational decision-making is crucial in clinical practices (Elwyn et al., 2012), healthcare (Hunink et al., 2014), business and knowledge management (García-Peñalvo & Conde, 2014), administration (Cremer, van Dick, Tenbrunsel, Pillutla, & Murnighan, 2011), politics (Le Breton, Montero, & Zaporozhets, 2012) and education (Bonal, 2012).

Digital device use has become increasingly prevalent due to technological advancements. However, those who use digital devices for economics-related purposes, such as e-commerce, do not necessarily possess the digital literacy and critical thinking skills needed to make well-informed economic decisions -- evidenced by the many who have fallen prey to e-commerce scams (Riefa, 2020). Principles of economics, such as efficiency, specialization, supply and demand (Barnett & Archambault, 2010) and cost-benefit analyses (Wiemer, 2012) have been incorporated into the gameplay of digital games, some of which have been designed to introduce students to economic concepts in the classroom (Ng, 2019). Research has been conducted on ethical decision-making in computer games (Sicart, 2009), but few empirical studies have examined players’ economic decision-making during gameplay in the context of various other factors such as different game types, player types and the significance of emotional attachment to characters.

In this study, we examined relevant economic concepts and how they can be applied to understand video game players’ decision-making processes. Then, we addressed the game studies field more directly by relating the economic considerations to other factors within gameplay activity. This study was guided by the following research questions.

  1. What economic concepts can be applied to understand players’ decision-making during gameplay?
  2. How are the economic considerations related to other factors within gameplay activity?

Literature Review

Lewis, Wardrip-Fruin and Whitehead (2012) applied behavioral economics and behavioral psychology to understand the appeal of social network games. They compared this to the appeal of games from the past and other human activities, and explained how these games motivate, engage and retain players. They identified motivational game design patterns by connecting multiple behavioral economics and behavioral psychology theories to explain the games’ popularity. Behavioral economics, the study of decision-making and behavioral psychology, applies cognitive psychology theories to analyze human decision-making. It focuses on anomalies from the standard economic model, such as irrational behavior that follows a decision that does not result in maximum gains (Lewis et al., 2012). Behavioral psychology aims to discover innate reactions to specific situations by examining organisms’ observable conduct when they change their voluntary behavior in response to a stimulus (Lewis et al., 2012). The behavioral economic theories used by these researchers included anchoring, the contrast effect, the endowment progress effect, hedonic treadmill, loss aversion, reciprocal altruism and the sunk cost fallacy. In the current study, loss aversion and the sunk cost effect were observed in video game players’ experiences and influenced their decision-making and behavior.

Miller and Watts (2011) reviewed economic concepts covered in children’s books published by Theodor Geisel (pen name Dr. Seuss), and discussed the author’s treatment of the concepts that appeared both in some depth and most frequently in his works. We adapted some of these concepts, including scarcity, choice, diminishing marginal utility and risk, in our paper to explain players’ decision-making during gameplay. Miller and Watts concluded their paper by explaining how economic concepts in Dr. Seuss’ canon can be used to teach economics. For instance, they suggested teaching basic economic concepts by requiring students to read and discuss passages that focused on economic content prior to class lectures on the relevant concepts. To teach more complex economic topics, they suggested using literary passages to provide examples and illustrations after the topic had been discussed in class with more traditional examples. In our paper, we conclude by briefly referring to the pedagogical potential of video games by suggesting that teachers can apply economic concepts to them as part of developing their students’ decision-making skills. We then suggest future research directions to this end.

Ng (2019) developed a video game called The Seven Wonders of Economics that can be played by students to gain an understanding of the hybrid principles of microeconomics. Gamification elements, such as badges and purchasable decorative items for players’ virtual houses, were used to reinforce students’ learning of economic concepts. The game’s seven modules were assigned to be played throughout the semester. Economic concepts covered by the game included the circular flow model, demand and supply, externalities, comparative advantage, types of market structure, sunk cost and game theory. Ng (2019) described the games’ modules in her paper, but did not test the game’s effectiveness in improving students’ learning outcomes. In contrast, our empirical data provided evidence of sunk cost, as well as sunk gain, being applied during gameplay decision-making.

Lawson and Lawson (2010) elicited learning theory principles from the literature that were embodied in commercially successful video games to guide development of instructional video game modules for teaching economics. The first module involved a simple storyline to bring to life economic concepts, such as diminishing marginal utility, the equimarginal principle of utility maximization, total and marginal physical product and the profit-maximizing level of output. The authors designed the module to accompany each cluster of chapters covered in a standard microeconomics course that together formed an adventure story. The second module, constructed by teams comprising two undergraduates and one incoming freshman working with faculty members, was envisioned to accompany chapters on the competitive firm theory. A basic story and gameplay puzzles portrayed productivity relationships, cost curves and profit maximizing behavior. In our study, the data revealed that diminishing marginal utility guided players’ decision-making.

Past studies have focused on how the economic principles are integrated in video game design. Higgins (2016) examined massively multiplayer online role-playing games to demonstrate how the game design planned for the obsolescence of goods to create infinite demand and endless commodity consumption as a mandatory feature of economic life in many digital environments. The investigation of the relationship between monetarization strategies, traditional game design and the creation of consumer commitment towards online games was the focus of Dreier et al.’s (2017) study. Based on a discussion of the design of microtransaction options in online games such as loot boxes, King and Delfabbro (2019) proposed the design and implementation of countermeasures for monetization schemes in game design. However, these studies focus on economics in game design and player behavior outcomes rather than apply economic concepts to study player decision-making processes during gameplay.


Participant Recruitment

The data was obtained from Toh’s (2018) study on player experience. For that study, advertisements were posted on our university’s website to recruit participants through convenience and snowball sampling. The Entertainment Software Association (2018) noted that gamers aged 18 or above represent 70% of the video game playing population, with an average age of 34. The age range of participants recruited for our sample in this study was 19 to 26. Of the 37 volunteers, only 11 completed the study, which involved playing through an entire game and participating in initial and final interviews. The data from 8 of these 11 participants were used for the current study. The eight participants were selected because they had at least five years of gaming experience and were familiar with the games chosen in the study. For instance, Participants 1 and 4 had watched YouTube gameplay videos of their selected games. We allowed participants to choose their game(s) from our curated list to maximize their enjoyment.

Gameplay Sessions

During the first session, participants completed a written survey to provide demographic information and gaming habits. While being observed, they played their selected game(s) from the beginning for one to three hours in a computer laboratory, where their gameplay was streamed and recorded using Fraps (computer) and a PS3 recorder. Their recordings served as references for each player to reflect on what they had learned from the playthrough. Players then verbalized their thoughts using retrospective think-aloud protocol. We conducted a one- to two-hour interview with participants after their first gameplay session and debriefed them by explaining the nature and aims of the study.

Participants were instructed to record their subsequent gameplay sessions at home and incorporate their natural reactions with their think-aloud verbalizations (using concurrent think-aloud protocol). Table 2 lists the numbers of subsequent sessions each participant completed. After completing their game(s) (approximately 14-30 hours), a final interview was held to review gameplay recordings and discuss their gaming experiences using retrospective think-aloud protocol and stimulated recall. In the final interview, we informed participants about the aims and nature of the study, and related the study’s aims to their experiences. Table 1 lists the number of recorded hours gathered per participant (for both think-aloud and interview recordings). The study was approved by the Institutional Review Board, and consent was obtained from participants to use their recordings for research purposes.


Table 1. No. of recording hours analyzed


Selected game

Think-aloud video recordings (hours analyzed)

Interviews (hours analyzed)






TWD Season 1/Eps. 1-3
































TWD Season 1/Eps. 1-5




TWD Season 1/Eps. 1-5




Data Coding

Theoretical thematic analysis was used in a deductive or “top down” way (e.g., Boyatzis, 1998; Hayes, 1997) to code the players’ decision-making thematically using economics concepts. With the theoretical thematic analysis approach, we are interested in how economics concepts can be applied to better understand the participants’ decision-making processes. We adopt a thematic analysis at the latent level that goes beyond the data’s semantic content, and examine the assumptions that theoretically shape or inform that content. In applying theoretical thematic analysis, the development of the themes themselves involves interpretative work such that the analysis that is produced is not just description but is already theorized (Braun & Clarke, 2006). Theoretical thematic analysis involves the use of theoretical frames from economics concepts to search across the data set in the form of think-aloud verbalizations, player reflections and player interviews to find repeated patterns of meaning. The steps involved in the theoretical thematic analysis involve familiarizing oneself with the data, generating initial codes, collating codes into themes, reviewing themes, defining themes and finally producing the report (Braun & Clarke, 2006).

Description of the Participants

Table 2 lists the profiles of each participant, who were full-time undergraduate students at our university. Their gaming habits primarily involved computer and some PlayStation gameplay several times per week. They preferred first-person shooters, action games, adventure games and sports games, and were motivated to play to experience both story and gameplay.


Table 2. Participants’ profiles




Gaming experience

Game(s) played

Gaming platform

No. of subsequent sessions




6-10 years

Bioshock and TWD Season 1/ Eps. 1-3


26 and 9




8 years

TW2 and ME


12 and 25




11-15 years







11-15 years


PS3 & Computer

8 and 14




11-15 years







>15 years







11-15 years

TWD Season 1/ Eps. 1-5






11-15 years

TWD Season 1/ Eps. 1-5




Description and Rationale of the Game Choices

Bioshock is a role-playing first-person shooter game set in a 1960’s underwater city. The player controls a character who is compelled to explore the city and liberate its inhabitants from servitude. Mass Effect (ME) is a role-playing third-person sci-fi shooter set in the future. The player controls Commander Shepard to save the galaxy from antagonists. The Walking Dead (TWD) is a graphic adventure game set in an apocalyptic world overrun by zombies. The player controls Lee Everett, who, accompanied by a group of survivors including a young girl called Clementine, explores the story world. The Last of Us (TLOU) is a role-playing third-person shooter set in a post-apocalyptic world of humans transformed into zombies by a mutated fungal strain. The player primarily controls Joel who is accompanied by a young girl called Ellie to explore the story world. The Witcher 2 (TW2) is set in a fantasy world shaped by Polish history and Slavic mythology. The player controls a monster hunter “Witcher,” who must clear his name by unravelling the mysterious identities of the antagonist and the organization that supported him to assassinate the Northern Kingdom kings.

These games were chosen because they required decision-making to manage limited resources, such as ammunition, health kits and character relationships. Choices in these games have both short- and long-term outcomes. Finally, the selected games were familiar to participants so that they could exercise critical thinking (reflection) during decision-making.


This section explains how we can understand the players’ decision-making during gameplay in light of economic concepts, such as return on investment and gratifications, sunk gain/cost, risk/loss aversion, scarcity of resources, cost-benefit analysis and emotions and economic decision-making (see Table 3).

Return on Investment and Gratifications

Behavioral economics applies psychological science to explain how people make economic decisions (Kamenica, 2012). The time-discounted utility theory is used in economics to describe subjective devaluation of outcomes as a function of time delay until delivery, where immediate rewards are more highly valued and more strongly influence our behavior than delayed rewards (Cai, Kim, & Lee 2011) -- especially for those who possess behavioral impulsivity and lower self-control (Jimura, Chushak, & Braver, 2013). Rewards are important factors that influence players’ decision-making in video games (Toh & Kirschner, 2020). Player behavior during gameplay is guided by reinforcement learning: where positive outcomes from a selected choice strengthen the stimulus-response connection, whereas negative outcomes weaken the connection (Toh & Kirschner, 2020). From a behavioral economics perspective, the utility function assumes decision-making is driven by the aim of maximizing utility, and that the utility function provides a way to quantify the subjective reward value the decision-maker attaches to each option (Elizabeth, Krishna, & Philippe, 2013).

Our data showed that Participant 1 was guided by the goal to maximize utility in her decision-making based on increasing returns and delayed gratification (as opposed to diminishing returns/marginal utility and immediate gratification) after she learned how the reward-based mechanics worked in Bioshock. Specifically, if she chose to harvest (kill) the non-player characters (NPCs), the little sisters, she would obtain more of the in-game ADAM resource, allowing her to upgrade her character more quickly. When she saved all of them, she obtained slightly less ADAM, but was rewarded with special “plasmid” powers from the little sisters’ presents. During the interview, Participant 1 noted the gameplay resource ADAM was not critical to her, as she chose to specialize on only a few powers such as Electro Bolt and Electric Flesh. Therefore, she decided not to kill the NPCs to obtain more resources for immediate gratification, as she did not need a lot of the ADAM resource. She perceived this resource from a diminishing returns perspective, which refers to the decreasing value of the gameplay resource, ADAM, after Participant 1 has completed upgrading the few powers that she chose to specialize in:

Initially, I did say I was going to try harvesting. … I was like maybe I could try harvesting because I can get more, but then, like, after getting the first two, the amount of ADAM that I can get right? I am like since, I mean, I’m not going to buy much [of] that…because for me I don’t do a lot of upgrades if you realized. … So, it’s like, to me, ADAM is not very critical to my progression. So, I was, like, okay, I’ll just save them.

Participant 1’s behavior was motivated by increasing returns over time and delayed gratification of the special plasmid powers that can only be obtained by saving the little sisters. She said she chose to save the little sisters for the special plasmid powers rewards that enabled her to maximize utility in relation to her play preference:

Then once I saved the third one, I suddenly get, like, the [plasmid] rewards from Tenenbaum. Then I was going to save all of them and get all the [plasmid] rewards. … Since then they repay you with some ADAM anyway. I think it’s not equivalent if you harvest them, but then I don’t need that much [ADAM] anyway, and they gave me plasmids. So, it’s paid off already…and I can get plasmid rewards anyway so…

We also observed Participant 2 in TW2 being guided by maximizing utility based on increasing returns and immediate gratification. He reflected that he could choose to perform repetitive behaviors, such as grinding, for experience and money at the same location in the game world instead of completing quests to level up his character faster:

In TW2 you are not forced to do the quest, you know? It is okay to miss the quest. Monster respawns and very easily, too, because TW2 has a meditation system, so you can actually, if you look at my recording of TW2, in act three near the end where I am doing the gargoyle, I realized I can actually grind on the gargoyles. So, all I have to do is kill all the gargoyles inside the room, walk out, meditate for two hours, which to me it’s like ten seconds, and then go back to the room and kill the gargoyles again. So, in two hours’ time, I actually made four to five thousand dollars, and I think increased by about two levels, which I think is very good for a casual gamer like me.

Sunk Gain/Cost and Risk/Loss Aversion

According to loss aversion in behavioral economics and decision theory, people tend to prefer avoiding losses to acquiring gains of the same value (Kahneman & Tversky, 1979; Brenner et al., 2007; Kahneman, 2011; Nguyen, 2016; Ruggeri et al., 2020). Loss aversion is related to the human preference to preserve the status quo against change (Gal, 2006), such as in cultural heritage preservation, where the most valuable parts of a cultural heritage must be conserved to benefit future generations (Holtorf, 2015). The loss aversion concept has also been found in stock investing (i.e., the disposition effect; Rau, 2014). Loss aversion describes the tendency for humans to continue investing in something that is not working (i.e., the sunk cost effect; Tykocinski & Ortmann, 2011; Magalhães & White, 2016). Studies (e.g., Polman, 2012) have also found that people who make choices for others reduces their loss aversion. When applying game theory, such as utility function and maximizing utility to game studies, it is worth noting that Kahneman’s work does not support the straightforward application of mathematical game theory to human decision making, as participants could also be influenced by other compounding factors -- such as their emotions or the game’s difficulty.

In Bioshock, Participants 1 and 3 restarted the little sisters’ escort mission whenever one of the NPCs was killed. Participants 1 and 3 had been choosing the option to save the little sisters throughout the game and had committed to the sunk gain -- which we define as opposite of the sunk cost -- where significant resources are invested into a decision, and can be redeemed later. Participants 1 and 3 did not want to incur a potential loss when the little sister died, as they perceived that they would obtain a bad ending if they allowed her to die. During the final interview, Participant 3 explained that he restarted the little sister escort mission to avoid this loss from the mission’s failure:

Interviewer: Did you reload the game for this part?

Participant 3: When it dies is it? Yes. I reload…Yes. Like if they die, then I start from a new save. I load from my save, right? Yes.

I: Yes. Did you think this part would have an outcome in the narrative or do you think that…

P3: Yes, I think there will be an outcome in the narrative.

I: So, you think you will make it the bad ending?

P3: Yes.

I: But, actually, there’s no outcome.

P3: Yes. I didn’t know. Just keep reloading.

Similarly, Participant 1 commented in the recording that she did not want the little sister to die during the escort mission. She reloaded her game when the NPC was low on health to keep her alive. “Come on! Stop it! She’s going to die. What should I do? I really do not want her to die, but I’m so bad at this. Shall I load? So sorry, I want her to live.”

Participant 2, who played Mass Effect, reflected in the recordings that allowing his squad members to die during gameplay would affect their relationship points with his player character. When Participant 2 had invested resources into developing a squad member, he could incur sunk costs if the squad member performed below expectations. For instance, instead of supporting the player character, the squad member might become a hindrance to the player if it repeatedly died during combat. Participant 2 mentioned that during gameplay he had no use for his squad member Garrus, the weakest character, because of his weak sniping ability. Additionally, the character’s artificial intelligence often failed to automatically take cover during combat, which contributed to Garrus’ repeated deaths whenever Participant 2 opted to play with him. As Mass Effect is a game that requires the player to complete specific side missions to build a relationship with the squad members, Participant 2 decided not to take Garrus on future missions to prevent him from dying. This, in turn, reduced Garrus’ overall relationship points with Shepard.

Participant 4 mentioned during an interview that he avoided the boss encounter in TLOU chapter five -- specifically, the Bloater fight with infected zombies in the Pittsburgh hotel basement. He decided to minimize his losses (or the sunk cost, i.e., time and effort to overcome enemies that cannot be recovered) by running from the infected zombies after triggering the encounter because he knew he lacked the materials (i.e., scarcity of resources) to fight in an enclosed space:

Some parts I was just lucky because it’s, like, for the hotel part, right? When we reached Pittsburgh, when we were going through the basement, after you fall from the lift into the basement, right? Some people encountered the Bloater, some people didn’t…But what I did was, I knew that the infected were going to come, so once I turned on the generator, I quickly ran so I could avoid the Bloater fight…[I didn’t want to fight in an enclosed place and] I don’t think I had much materials. Maybe I didn’t do something that [doesn’t] trigger the infected? I don’t know.

Scarcity of Resources

Insufficient resources can contribute to a scarcity mindset and increase attention towards scarce resources, but at the cost of attention to unrelated aspects (Huijsmans et al., 2019). Prior research has examined how a scarcity mindset influences consumer decision-making. Shah, Shafir and Mullainathan (2015) argued that a scarcity mindset might render people more contemplative and, thus, less susceptible to external influences when making choices about resources. Conversely, under conditions of economic hardship, evidence has shown people’s behaviors were influenced by factors unrelated to resource scarcity, such as when poverty is associated with high caloric food intake (Drewnowski & Specter, 2004; Bratanova, Loughnan, Klein, Claassen & Wood, 2016) and when income inequality leads to increased consumption of higher-status or positional goods (Van Kempen, 2003; Moav & Neeman, 2012).

Resource scarcity has been found to influence player behavior. During the interview, Participant 5 mentioned one challenging aspect of Bioshock’s world was its lack of resources. This scarcity of resources was different than in other games, where he could find many resources, such as ammunitions and health packs. As a result, his behavior became deliberative, as he had to consider conserving ammunition and plan his actions before performing them. For instance, he mentioned before he fought a Big Daddy (a heavily armored enemy in Bioshock), he purposefully conserved armor piercing rounds in preparation for the fight. During the fight, he switched to the pistol and used armor piercing rounds to damage the Big Daddy until he realized that the best tactic was to fight it head on due to the confined combat area.

Similarly, Participants 4 and 6, who played TLOU, highlighted during their interviews how the scarcity of in-game resources influenced how they controlled Ellie, the player character during the game’s winter chapter. Participant 6 mentioned that when Ellie ran from the antagonist David after he failed to convince her to join his group, she only had one health pack and one dagger. The scarcity of resources influenced Participant 6 into feeling more concerned about the type of actions she could perform with Ellie. She was forced to play more stealthily and more conservatively, and snuck around carefully to avoid being killed by David’s men. Similarly, Participant 4 mentioned during his interview that he treasured health kits more when he played as Ellie compared to Joel, and learned how to sneak around more as Ellie to prioritize her survival:

I treasured my health kits more because I knew that I needed more practice with the stealth. Since I am not that good at stealth, I would probably fail more, so I would probably need more health kits…but once I had sufficient health kits, I realized that since she was going for more of the stealth option, I could make stuff like trap bombs and stuff like that to help the process. … I think even with Joel, I still treasured the health kits but perhaps more with Ellie, and I am not too sure whether there is a difference, but in general I do treasure health kits.

Cost-benefit Analysis

Cost-benefit analysis is an economics process that identifies, measures, and compares benefits and costs of an investment project or program (Campbell & Brown, 2016). A program involves a series of projects undertaken over time with a specific objective, whereas a project involves a proposed course of action that reallocates productive resources from their present use to undertake the project (Campbell & Brown, 2016). The reallocation of productive resources involves opportunity cost, which refers to the benefits (or value) that would have been produced had resources not been reallocated for other projects to produce other benefits for the decision-maker. When the player makes decisions during gameplay, the benefits of a decision usually need to be weighed against accompanying costs. Cost-benefit-based decision-making involves the binary decision to either accept or reject a choice according to two competing attributes: expected rewards and expected losses (Basten, Biele, Heekeren, & Fiebach, 2010).

In TWD Season 1/Episode 1, Participants 1, 7 and 8 chose to rescue Carley when the group escaped from a pharmacy overrun by zombies. When reflecting on his decision-making, Participant 7 mentioned that he had saved Carley because the benefit of saving her outweighed the cost of losing her if he chose to save the other NPC, Doug:

It is not because she’s a girl, so I chose Carley and not Doug. But it’s because, like I say, it’s more practical to save a person with a more accurate shot who has more experience in guns than saving someone that is technologically wiser. Like, especially now, zombie land, it’s like, it’s more useful to be able to kill zombies than program something. I think if I were Lee, I would choose to keep Carley also. I would rather have both together, but if I must make a choice, I would choose Carley over Doug.

Similarly, Participant 1 reflected on why she chose to save Carley because, as a player, she felt closer to Carley, as she had spent more time with Carley than with Doug. Therefore, she had a deeper understanding of Carley’s essential role in the game and realized the benefit of saving her over Doug:

I chose Carley. She is a good shot, and we know her better…[in] Walking Dead, I realized that they showed who the so-called main characters are more clearly. I hardly know about Doug to be honest. We didn’t really talk much. He only assisted me in the part where I go outside, so in a sense, the bonding wasn’t there, but for Carley it was different. She went with Lee to the Motel Inn, and there was a sort of, you know, like a bond during that time…as a player, I felt closer to Carley than Doug, and I felt Carley was more essential…than Doug…I guess Carley would have been a better choice, especially since she is good with a gun there, and I didn’t even know what Doug can do to be honest.

At the end of TWD Season 1/Episode 4, a zombie bit Participant 7’s character Lee Everett on the wrist when he went looking for Clementine, who had disappeared. During the interview, Participant 7 explained how cost-benefit analysis guided how he weighed whether or not to saw off Lee’s arm to prevent infection. He mentioned that there was a greater cost to sawing off Lee’s arm, as it would potentially make it harder to find Clementine. In contrast, he perceived choosing to keep Lee’s infected arm as more practical, because he believed doing so would make saving Clementine easier. This perceived benefit guided Participant 7 to choose not to saw off Lee’s arm:

Participant 7: Then the main goal was to save Clementine and then…get the stranger out of the picture. Then to do to do that, and to save her, and to prevent him [the stranger] from coming back to us, then I probably have to…

Interviewer: Yeah, you say that it’s more practical.

P7: Yeah, it’s more practical, more practical to keep the arm. Like two arms is better than one obviously. Even though I got bitten. But it’ll take a while, like how we saw Duck. It just that I will die [eventually]. After this, I realize, I decide that the main goal was to save Clementine; whether I die or not doesn’t matter.

Emotions and Economic Decision-making

Economic decision-making models assume decision-makers can make choices by weighing the desirability (utility) and likelihood of their consequences (e.g., maximizing utility), and by integrating information into the decision-making process (Rick & Loewenstein, 2008). What happens, then, when actors don’t possess sufficient information and must make choices under uncertain conditions? Under such conditions, actors may be guided by their emotions (Lerner, Li, Valdesolo, & Kassam, 2015), intuitions, heuristics, prior experiences, biases (e.g., loss aversion) and personalities (Kahneman, 2011; Stojanović, 2013) -- especially when under time constraints. Participant 8 discussed during his interview how TWD featured dialogue-based, time-constrained decisions that simulated the pace of real-life conversations. He felt pressured to think fast and respond during these sequences, and found these dialogue choices difficult to make. This environment may contribute to an irrational decision-making process (Thaler & Sunstein, 2008) due to the asymmetrical information possessed by an individual.

In TWD Season 1/Episode 2, Participant 1 was forced to choose from among equally bad conversational options when talking to Kenny about the group’s future. Kenny had just killed Lily’s father, and Participant 1 possessed insufficient information to fully understand the outcomes of the options available to her. In terms of maximizing utility, selecting any of the negative options seemed to entail the cost of straining the player-character’s relationship with Kenny. As such, Participant 1 felt she could not derive utility (i.e., satisfaction) from her limited choices. She relied on her prior experience interacting with Kenny in the game and took a risk (Tversky & Kahneman, 1981) by selecting the choice, “You murdered Larry” while exclaiming, “Damn, what should I say? They are all bad options!” After choosing, she reflected, “Oh damn, am I going to split up with Kenny?” indicating her emotional response and loss aversion bias. During the final interview, Participant 1 clarified that when making decisions with equally poor options that both clashed with her personality and had unclear outcomes, she found it more difficult to choose due to loss aversion.

Similarly, Participant 8 mentioned during his interview about TWD that he prioritized intuitions, emotions and prior experience over maximizing utility when deciding whether to save a character or to allocate limited resources among different NPCs -- especially when he had insufficient information to decide within a time constraint:

So, a little bit of instinct, mainly of what I would probably do in real life. There is actually some experience in other games that I used here…Then in terms of age, children are always a priority. Then friends and family are priority. Top two priorities. Then the third priority would be how much of, er, but you cannot really say that these priorities are isolated from each other. I’ll have to consider them all. There will be some priorities that overwrite other priorities, but there will be some scenarios, those priorities actually depend on each other…For this game, kids first, then friends, then whoever is useful.

Table 3 summarizes the economic concepts that guided the participants’ decision-making during gameplay.


Table 3. Economic concepts and decision-making

Economic concepts



Return on investment and gratifications

Decisions are made on maximizing utility over time.

Participants 1, 3 and 5 chose to save the little sisters in Bioshock.

Sunk gain/cost and risk/loss aversion

Decisions are made and actions planned to avert losses from sunk cost/gain.

Participant 2 chose not to take Garrus on missions in ME.

Scarcity of resources

Decisions are made and actions taken to conserve resources.

Participant 5 conserved special ammunition for boss fights in Bioshock.

Cost-benefit analysis

Decisions are made by evaluating gains and losses involved in available options.

Participants 1, 7 and 8 chose to save Carley over Doug in TWD.

Emotions and economic decision-making

Decisions are made using prior experience (e.g., emotions and bias) under time-constrained conditions with limited information.

Participant 1 was guided by loss aversion bias when it was difficult to make a choice in TWD.


In this section, we will relate the economic considerations to other factors within gameplay activity such as different game types, player types and the significance of emotional attachment to characters.

Economic Considerations and Game Types

The game type may affect whether the player can focus on the economic decision-making during gameplay or whether other factors are more significant. In real-time strategy games such as Age of Empires, the economic principles such as investment, capital, diminishing returns to labor, cost and benefits of different technologies and scarcity of resources (Assa, 2013) are foregrounded in the decision-making process. In such games, players are tasked with gathering resources to develop an economy, and raising an army to defeat opposing forces. In turn-based strategy games such as the Civilization series, the players’ objective is to take control of a band of settlers in 4000 BC and build an empire to ultimately take over the world. To play these games, players must make decisions, such as choosing the economy that best suits their landscape, balancing industrial progress with environmental preservation and engaging in the cost-benefit analysis of being involved in wars with other nations. A healthy economy because of the players’ decision-making is one of the victory conditions in Civilisation VI. The story-driven games that are the focus of this paper may obscure the economic basis of choices for the type of players who like to immerse themselves in a story-world, role-play as a player character and form affective relationships with the other characters. For instance, Participant 2 reflected that what he liked about TW2 was that he could focus on the game’s storyline instead of putting too much effort into the gameplay -- as the game did not force him to complete side quests in order to gather resources for equipment and potions.

The economic principles of wealth depreciation, taxation and unemployment do not exist in multi-player games such as Eve Online (Hooper, 2020). The lack of these economic principles in such online games helps to create a safe space for players; enabling them to stop playing whenever they choose without risking losing any in-game assets. However, wealth inequality exists in multi-player games such as Eve Online and is strongly correlated with the amount of time players have invested in the game (Hooper, 2020). The economic principle of return on investment is then important for the type of player who decides to invest more time into playing. The economic principle of return on investment can also manifest through pay-to-win features, or “microtransactions,” in online games (King & Delfabbro, 2019; King et al., 2020) in which players can not only pay to get immediate gratification by unlocking new game content (Salminen et al., 2018), but also to express their economic commitment in hopes of being acknowledged by other players for it (Nielsen, 2020).

The economic principle of wealth inequality is also applicable to open world games, such as Minecraft. The study of player decision-making processes can occur on both the micro level of individual player choice, as well as on the macro level of Minecraft’s economy servers; in which all of the players’ respective wealth data is collected to understand the impact of unregulated economies on wealth inequality in-game (Blackwell & Carroll, 2018). Economic decision-making can also be found in online linear games, such as McKinney and Urban Ministries of Durham’s Spent. Spent teaches players how poverty affects one’s decision-making processes by allowing them to play as a person who is living on the edge of poverty. During gameplay, players must make difficult decisions to survive for one month on a one-thousand-dollar budget. The cost and benefits of each player’s choices are clearly shown on screen for players to see the consequences of their choices.

Economic Considerations and Player Types

Although our study did not examine the relationship between player types and different economic considerations, we can infer the significance of economic considerations to different player types. Yee’s (2007) empirical model of player motivations in online games may be adapted for discussion. Some of Yee’s categories, such as the “achievers” or “immersion players,” may be more applicable toward single-player, story-driven games, as opposed to the “socializer” category, which is more applicable to online games.

According to Yee’s (2007) model, the achiever player type is defined as players who are driven to accrue power, rare items and collectibles in-game. Achievement is motivated by completion, which includes the desire to complete every mission, get every collectible and discover hidden things -- as well as power, which refers to the significance of becoming powerful in the game world. The achiever player type might be applied to Participant 3, who was more interested in gameplay. Economic considerations such as cost-benefit analysis and return on investment may be more important to him, as his decision-making was motivated by creating a powerful character, and by experimenting with different gameplay strategies to overcome gameplay challenges. However, this does not mean that other economic considerations, such as loss aversion, were not applicable to this player, just that they were less important.

In contrast, the immersion player type is motivated by fantasy and story, as they become immersed in a story with an elaborate storyline and interesting characters. The immersion player type may be more applicable to Participants 1, 2, 4, 5, 6, 7 and 8 who were interested in the game’s story and characters. For these players, the economic consideration of loss aversion may be more important to them, as their decision-making was driven by a need to preserve their relationships with characters they were connected to; as well as avoiding losing characters whom they had become emotionally invested in. However, this does not mean that other economic considerations, such as cost-benefit analysis, were not applicable to these players, just that they were less important.

Loss Aversion and Emotional Connection to Characters

The loss of a character can have consequences for both gameplay and game narrative, and can have an influence on the player’s emotional state (Harrer, 2013). Character attachment heavily influenced our participants’ feelings, as many expressed sadness when they lost a character or left behind a character they cared about (Bopp et al., 2016). Additionally, for some players, the experience of in-game loss brought back memories of personal loss, which increased their emotional responses (Bopp et al., 2016).

In story-driven games, players are required to decide which characters to save, sacrifice, or side with. Participant 1 reflected that it was hard for her to make a choice when the game forced her to choose an option that caused her character’s relationship with an emotionally invested character, Kenny, to deteriorate in TWD. For instance, Participant 1 was forced to choose amongst equally bad options when her character, Lee Everett, spoke to Kenny at the end of TWD Episode 2 -- Kenny responded to her character by saying that Lee did not support him when he chose to kill Larry in the meat locker. Her think-aloud reflections expressed her loss aversion when she commented that her character was about to “split up” with Kenny and she could not do anything about it. Concerning ME, Participant 4 reflected on how he chose the “calm down” option to save his squad member, Wrex, in one of the missions, but the outcome of selecting that choice was that Wrex was killed instead. Due to his emotional investment in the character, as well as the time and effort spent in building up the character’s gameplay attributes, he replayed that part of the mission and chose another option “These aren’t your people” so that he could save Wrex and not lose him.

In this study, emotional relations might not be put into the same loss-aversion schema as in-game resources. This is because most of the participants, including Participants 1, 2, 4, 5, 6, 7 and 8, tried to think of what they would do in the game world based on what they would do in a comparable situation in real life. It is worth noting that these were the participants who reportedly cared more about the game’s story and characters as opposed to gameplay. These participants would try to be prosocial and do what they felt was the right way to treat the story’s NPCs just as they would treat other human beings in the real-world. In contrast, Participant 3 -- who was more interested in gameplay rather than his game’s story -- controlled his character more as an avatar to explore gameplay strategies and complete objectives for rewards. The extent to which emotional relations might not be put into the same loss-aversion schema as in-game resources also depends on the game type. Participants 1, 3 and 5 who played Bioshock mentioned that they could not relate to the player character they were controlling, as he was a silent character with little-known background. In contrast, for the games that featured voiced characters, such as TWD, TW2, ME and TLOU, Participants 1, 2, 4, 6, 7 and 8 expressed that they were able to understand these characters better than the silent protagonists of other games. They were more interested in learning about these characters’ stories by interacting more with them in the story world. When they lost some of these characters permanently while playing the game, such as when Participant 4 sacrificed Kaiden to save Ashley in ME, their loss aversion was more related to the story rather than experiencing the characters’ losses as in-game resources. This loss aversion was reflected in the participants’ deliberations while deciding which character to lose.

The main factor that helped each participant achieve the ideal of rational decision-making was when they possessed more complete information about the game, such as knowing the consequences of selecting specific conversational or gameplay choices. Participants 1, 4, 6 and 8 had either watched YouTube videos of their selected game, or had previously played their game at least once before the study. Participants that did so possessed a greater understanding of choices that would help them maximize their return on investment during economic decision-making. Such choices included those that would help them preserve relationship with other NPCs or side characters to get a specific story ending or gameplay reward. In contrast, Participants 2, 3, 5 and 7 (who had no prior knowledge of their games), did not know how to maximize their return on investment in their economic decision-making during gameplay. They would play the game by relying on their prior gaming and real-life experience, or use trial and error strategies to figure out how to achieve the ideal of rational decision-making during gameplay.


In this study, we have used theoretical thematic analysis to understand how economics concepts can be applied to better understand our participants’ decision-making process during gameplay. Then we addressed the game studies field more directly by relating economic considerations to other factors within gameplay activity. One of the study’s limitations involves the method we adopted for the study. Besides the think-aloud protocol, we also asked participants during the final interview to reflect on their decision-making after they completed their game. Because they had completed the game, they possessed foreknowledge of the game that was used to complement our understanding of their decision-making processes. Therefore, a lot of the analysis relies on post-hoc rationalization. Another limitation of this study is the gender bias of the selected participants, as there were more male participants than females due to the snowball and convenience sampling method used. The selected games in this study were action and adventure games, and the story-world immersion and affective relations to characters may obscure the economic basis of choices for many players. Future research can be conducted on other game types, such as simulation and real-time strategy games, to investigate other economic concepts guiding players’ decision-making during gameplay.

Finally, video games can be used for learning (Squire, 2002; Gee, 2003; Toh & Lim, 2021). Pedagogical programs have applied psychological theories to teach decision-making to adolescents (Baron & Brown, 2012). However, studies that investigate using video games to teach decision-making through economic concepts are lacking, despite evidence that interventions using computer games can improve decision-making skills (e.g., Morewedge et al., 2015). In this qualitative study, we did not evaluate the effectiveness of using video games for teaching decision-making through economic concepts in the classroom. Future research can investigate how commercial video games or educational games can be integrated in the classroom for teaching decision-making through economic concepts (e.g., Ng 2019). Such research might compare this approach with the normal method of teaching economic concepts in the classroom to discover if using video games can motivate students more, and help them better understand economic concepts.



The PhD work, on which this research draws, was funded by the National University of Singapore. The empirical study was partially funded by the National Youth Council’s National Youth Fund (NYF) grant and was carried out at the National University of Singapore. I thank the three anonymous reviewers whose comments helped improve and clarify the manuscript. Thanks also to the participants who took part in the study and Ryan Wright for editing and formatting the article on the website for publication.



2K Boston. (2007). Bioshock [Microsoft Windows]. Digital game directed by Ken Levine, published by 2K Games.

Assa, J. (2013). The Age of Models: Economic Lessons in Real-Time Computer Strategy Games. SSRN. https://ssrn.com/abstract=2334348 or http://dx.doi.org/10.2139/ssrn.2334348

Barnett, J. H., & Archambault, L. (2010). The Gaming Effect: How Massive Multiplayer Online Games Incorporate Principles of Economics. TechTrends, 54(6), 29-35. https://doi.org/10.1007/s11528-010-0451-y

Baron, J., & Brown, R. V. (2012). Teaching Decision Making to Adolescents. New York: Routledge.

Basten, U., Biele, G., Heekeren, H. R., & Fiebach, C. J. (2010). How the brain integrates costs and benefits during decision making. Proceedings of the National Academy of Sciences of the United States of America, 107(50), 21767-72. https://doi.org/10.1073/pnas.0908104107

BioWare. (2007). Mass Effect [Microsoft Windows]. Digital game directed by Casey Hudson, published by Microsoft Game Studios.

Blackwell, C., & Carroll, J. (2018). Minecraft Economics: A Study of Wealth Inequality in a Virtual World. SSRN. https://ssrn.com/abstract=3185048 or http://dx.doi.org/10.2139/ssrn.3185048

Bonal, X. (2012). Education policy and school segregation of migrant students in Catalonia: the politics of non-decision-making. Journal of Education Policy, 27(3), 401-421. https://doi.org/10.1080/02680939.2011.645168

Bopp, J. A., Mekler, E. D., & Opwis, K. (2016). Negative Emotion, Positive Experience?: Emotionally Moving Moments in Digital Games. CHI’16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 2996-3006. https://doi.org/10.1145/2858036.2858227

Boyatzis, R. E. (1998). Transforming qualitative information: thematic analysis and code development. Sage.

Bratanova, B., Loughnan, S., Klein, O., Claassen, A., & Wood R. (2016). Poverty, inequality, and increased consumption of high calorie food: Experimental evidence for a causal link. Appetite, 100, 162-171. https://doi.org/10.1016/j.appet.2016.01.028

Braun, V., & Clarke, V. (2006). Using thematic analysis in Psychology. Qualitative Research in Psychology, 3, 77-101.

Brenner, L., Rottenstreich, Y., Sood, S., & Bilgin, B. (2007). On the psychology of loss aversion: Possession, valence, and reversals of the endowment effect. Journal of Consumer Research, 34(3), 369-376.

Cai, X., Kim, S., & Lee, D. (2011). Heterogeneous Coding of Temporally Discounted Values in the Dorsal and Ventral Striatum during Intertemporal Choice. Neuron, 69(1), 170-182. https://doi.org/10.1016/j.neuron.2010.11.041

Campbell, H. F., & Brown R. P. C. (2016). Cost-benefit analysis: Financial and economic appraisal using spreadsheets. London and New York: Routledge.

CCP Games. (2003). Eve Online [Microsoft Windows]. Digital game published by Simon & Schuster.

CD Projekt RED. (2012). The Witcher 2: Assassins of Kings [Microsoft Windows]. Digital game published by Atari.

Cremer, D. D., van Dick, R., Tenbrunsel, A., Pillutla, M., & Murnighan, J. K. (2011). Understanding Ethical Behavior and Decision Making in Management: A Behavioural Business Ethics Approach. British Journal of Management, 22(1), 51-54. https://doi.org/10.1111/j.1467-8551.2010.00733.x

Drewnowski, A., & Specter, S. E. (2004). Poverty and obesity: The role of energy density and energy costs. The American Journal of Clinical Nutrition, 79, 6-16. https://doi.org/10.1093/ajcn/79.1.6

Dreier, M., Wölfling, K., Duven, E., Giralt, S., Beutel, M. E., & Müller, K. W. (2017). Free-to-play: About addicted Whales, at risk Dolphins and healthy Minnows. Monetarization design and Internet Gaming Disorder. Addictive Behaviors, 64, 328-333.

Elizabeth, H. Z., Krishna, P. M., & Philippe, N. T. (2013). Understanding consumer decisions using behavioral economics. In P. V. S. Chandrasekhar, & S. Narayanan (Eds.), Decision Making - Neural and Behavioural Approaches (pp. 197-211). Amsterdam: Elsevier.

Elwyn, G., Frosch, D., Thomson, R., Joseph-Williams, N., Lloyd, A., Kinnersley, P. et al. (2012). Shared Decision Making: A Model for Clinical Practice. Journal of General Internal Medicine, 27, 1361-1367. https://doi.org/10.1007/s11606-012-2077-6

Ensemble Studios. (1997). Age of Empires [Microsoft Windows]. Digital game published by Xbox Game Studios.

Entertainment Software Association. (2018). Essential facts about the computer and video game industry. Retrieved from https://www.theesa.com/wp-content/uploads/2021/03/ESA_EssentialFacts_2018.pdf

Gal, D. (2006). A Psychological Law of Inertia and the Illusion of Loss Aversion. Judgment and Decision Making, 1(1), 23-32.

García-Peñalvo, F. J., & Conde, M. Á. (2014). Using informal learning for business decision making and knowledge management. Journal of Business Research, 67(5), 686-691. https://doi.org/10.1016/j.jbusres.2013.11.028

Gee, J. P. (2003). What Video Games Have to Teach Us About Learning and Literacy. Palgrave/Macmillan.

Harrer, S. (2013). From losing to loss: Exploring the expressive capacities of videogames beyond death as failure. Culture Unbound: Journal of Current Cultural Research, 5(4), 607-620.

Hayes, N. (1997). Theory-led thematic analysis: social identification in small companies. In Hayes, N. (Ed.), Doing qualitative analysis in psychology (pp. 93-114). Psychology Press.

Higgins, D. M. (2016). Dreams of accumulation: the economics of SF video games. Science Fiction Studies, 43(1), 51-66.

Holtorf, C. (2015). Averting loss aversion in cultural heritage. International Journal of Heritage Studies, 21(4), 405-421. https://doi.org/10.1080/13527258.2014.938766

Hooper, B. (2020). EVE Online: The Worlds of Wealth and War. Proceedings of DiGRA 2020, 1-13.

Huijsmans, I., Ma, L., Micheli, L., Civai, C., Stallen, M., & Sanfey, A. G. (2019). A scarcity mindset alters neural processing underlying consumer decision making. Proceedings of the National Academy of Sciences of the United States of America, 116(24), 11699-11704. https://doi.org/10.1073/pnas.1818572116

Hunink, M. G., Weinstein, M. C., Wittenberg, E., Drummond, M. F., Pliskin, J. S., Wong, J. B., et al. (2014). Decision Making in Health and Medicine -- Integrating Evidence and Values. Cambridge, United Kingdom: Cambridge University Press.

Jimura, K., Chushak, M. S., & Braver, T. S. (2013). Impulsivity and Self-Control during Intertemporal Decision Making Linked to the Neural Dynamics of Reward Value Representation. The Journal of Neuroscience, 33(1), 344-357. https://doi.org/10.1523/JNEUROSCI.0919-12.2013

Kahneman, D. (2011). Thinking, Fast and Slow. New York: Farrar, Straus and Giroux.

Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-291.

Kamenica, E. (2012). Behavioral Economics and Psychology of Incentives. Annual Review of Economics, 4, 427-452. https://doi.org/10.1146/annurev-economics-080511-110909

King, D. L., & Delfabbro, P. H. (2019). Video Game Monetization (e.g., ‘Loot Boxes’): a Blueprint for Practical Social Responsibility Measures. International Journal of Mental Health and Addiction, 17, 166-179.

King, D. L., Russell, A. M. T., Delfabbro, P. H., & Polisena, D. (2020). Fortnite microtransaction spending was associated with peers’ purchasing behaviors but not gaming disorder symptoms. Addictive Behaviors, 104, 1-7.

Lawson, C. L., & Lawson, L. L. (2010). Adventures in Learning: Creating Role Playing Video Games to Teach and Learn Economics. International Review of Economics Education, 9(1), 93-110. https://doi.org/10.1016/S1477-3880(15)30058-X

Le Breton, M., Montero, M., & Zaporozhets, V. (2012). Voting power in the EU council of ministers and fair decision making in distributive politics. Mathematical Social Sciences, 63(2), 159-173.

Lerner, J. S., Li, Y., Valdesolo, P., & Kassam, K. S. (2015). Emotion and Decision Making. Annual Review of Psychology, 66, 799-823. https://doi.org/10.1146/annurev-psych-010213-115043

Lewis, C., Wardrip-Fruin, N., & Whitehead, J. (2012). Motivational Game Design Patterns of ‘Ville Games. In FDG '12: Proceedings of the International Conference on the Foundations of Digital Games, 172-179. https://doi.org/10.1145/2282338.2282373

Magalhães, P., & White, K. G. (2016). The sunk cost effect across species: A review of persistence in a course of action due to prior investment. Journal of the Experimental Analysis of Behavior, 105(3), 339-361. https://doi.org/10.1002/jeab.202

McKinney and Urban Ministries of Durham. (2011). Spent [Online Game]. Digital game published by McKinney. Accessed September 18, 2021. http://playspent.org/

MicroProse. (1991-2016). Sid Meier's Civilization series [Microsoft Windows]. Digital games directed by Sid Meier, published by MicroProse.

Miller, B., & Watts, M. (2011). Oh, the Economics You’ll Find in Dr. Seuss! The Journal of Economic Education, 42(2), 147-167. https://doi.org/10.1080/00220485.2011.555717

Moav, O., & Neeman, Z. (2012). Saving rates and poverty: The role of conspicuous consumption and human capital. The Economic Journal, 122(563), 933-956. https://doi.org/10.2139/ssrn.1727272

Mojang. (2011). Minecraft [Microsoft Windows]. Digital game published by Mojang.

Morewedge, C. K., Yoon, H., Scopelliti, I., Symborski, C. W., Korris, J. H., & Kassam, K. S. (2015). Debiasing Decisions: Improved Decision Making with a Single Training Intervention. Policy Insights from the Behavioral and Brain Sciences, 2(1), 129-140. https://doi.org/10.1177%2F2372732215600886

Naughty Dog. (2013). The Last of Us [PlayStation 3]. Digital game directed by Neil Druckmann, published by Sony Interactive Entertainment.

Ng, C. F. (2019). A video game to supplement a hybrid principles of microeconomics course. The Journal of Economic Education, 50(1), 44-56. https://doi.org/10.1080/00220485.2018.1551101

Nguyen, Q. (2016). Linking loss aversion and present bias with overspending behavior of tourists: Insights from a lab-in-the-field experiment. Tourism Management, 54, 152-159.

Nielsen, D. (2020). The moral economy of micro-transactions in digital games. Baltic Screen Media Review, 8(1), 93-110.

Polman, E. (2012). Self-other decision making and loss aversion. Organizational Behavior and Human Decision Processes, 119(2), 141-150. https://doi.org/10.1016/j.obhdp.2012.06.005

Rau, H. A. (2014). The disposition effect and loss aversion: Do gender differences matter? Economics Letters, 123(1), 33-36. https://doi.org/10.1016/j.econlet.2014.01.020

Rick, S., & Loewenstein, G. (2008). The Role of Emotion in Economic Behavior. In M. Lewis, J. M. Haviland-Jones, & L. F. Barrett (Eds.), Handbook of Emotions (pp. 138-156). 3rd ed. New York: The Guilford Press.

Riefa, C. (2020). Consumer Protection on Social Media Platforms: Tackling the Challenges of Social Commerce. In T. E. Synodinou, P. Jougleux, C. Markou, & T. Prastitou (Eds.), EU Internet Law in the Digital Era (pp. 321-345). Cham, Switzerland: Springer.

Ruggeri, K., Ali, S., Berge, M. L., Bertoldo, G., Bjørndal, L. D., Cortijos-Bernabeu, A., Davison, C., Demić, E., Esteban-Serna, C., Friedemann, M., Gibson, S. P., Jarke, H., Karakasheva, R., Khorrami, P. R., Kveder, J., Andersen, T. L., Lofthus, I. S., McGill, L., Nieto, A. E., … Folke, T. (2020). Replicating patterns of prospect theory for decision under risk. Nature Human Behaviour, 4, 622-633.

Salminen, M., Järvelä, S., & Ravaja, N. (2018). Economic decision-making in free-to-play games: A laboratory experiment to study the effects of currency conversion. Proceedings of the 2nd International GamiFIN Conference Pori, Finland, May 21-23, pp. 92-99. CEUR.

Shah, A. K., Shafir, E., & Mullainathan, S. (2015). Scarcity frames value. Psychological Science, 26, 402-412. https://doi.org/10.1177/0956797614563958

Sicart, M. (2009). The ethics of computer games. The MIT Press.

Spires, H. A., & Lester, J. C. (2016). Game-based learning: creating a multidisciplinary community of inquiry. On the Horizon, 24(1), 88-93.

Squire, K. (2002). Cultural Framing of Computer/Video Games. Game Studies: The International Journal of Computer Game Research, 2(1).

Stojanović, B. (2013). Daniel Kahneman: The riddle of thinking: Thinking, fast and slow, Penguin books, London, 2012. Panoeconomicus, 60(4), 569-576.

Telltale Games (2012). The Walking Dead [Microsoft Windows]. Digital game published by Telltale Games.

Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving Decisions About Health, Wealth, and Happiness. London, England: Penguin Books.

Toh, W. (2018). A Multimodal Approach to Video Games and the Player Experience. New York: Routledge.

Toh, W., & Kirschner, D. (2020). Self-directed learning in video games, affordances and pedagogical implications for teaching and learning. Computers & Education, 154, 1-11.

Toh, W., & Lim, F. V. (2021). Using Video Games for Learning: Developing a Metalanguage for Digital Play. Games and Culture, 16(5), 583-610.

Tversky, A, & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4481), 453-458. https://doi.org/10.1126/science.7455683

Tykocinski, O. E., & Ortmann, A. (2011). The Lingering Effects of Our Past Experiences: The Sunk‐Cost Fallacy and the Inaction‐Inertia Effect. Social and Personality Psychology Compass, 5(9), 653-664. https://doi.org/10.1111/j.1751-9004.2011.00369.x

Van Kempen, L. (2003). Fooling the eye of the beholder: Deceptive status signalling among the poor in developing countries. Journal of International Development, 15, 157-177. https://doi.org/10.1002/jid.973

Wiemer, S. (2012). Interface Analysis: Notes on the “Scopic Regime” of Strategic Action in Real-Time Strategy Games. In J. Fromme, & A. Unger (Eds.), Computer Games and New Media Cultures: A Handbook of Digital Games Studies (pp. 75-91). New York and London: Springer.

Yee, N. (2007). Motivations of Play in Online Games. Journal of CyberPsychology and Behavior, 9, 772-775.

©2001 - 2021 Game Studies Copyright for articles published in this journal is retained by the journal, except for the right to republish in printed paper publications, which belongs to the authors, but with first publication rights granted to the journal. By virtue of their appearance in this open access journal, articles are free to use, with proper attribution, in educational and other non-commercial settings.