The Impact of Social Value Orientation,Game Context and Trust on Cooperative Behavior After Cooperative Video Game Play

Abstract

This study explores the effects of the cooperative video game context, social value orientation (SVO) and trust on cooperative behavior. The main ﬁnding is that collaborative game play signiﬁcantly increases cooperative behavior, especially in prosocial individuals. In addition, a mediation model is established in which trust partially mediates the association between the game mode and cooperative behavior. The results indicate that playing collaborative games increases cooperation in prosocial people partially by facilitating the trust they have in their gaming partners. The theoretical and practical implications of these findings are discussed.

Keywords

Cooperative behavior game context social value orientation trust cooperative video game

Introduction

By the end of December 2018, the number of Internet users in China had reached 829 million, and the Internet penetration rate was 59.6%. Among Internet users, the number of online game users in China had reached 484 million, accounting for 58.4% of all Internet users (The 43^rd Statistical Report on the Development of the Internet in China, 2019). The age range of online game users is mainly 10–39 years old. Video games have become the main form of entertainment for young people, and the influence of games on the psychology and behavior of young people has gradually become an important issue for researchers and society.

Literature review

Game content

A meta-analysis showed that depending on the game content, video games affect social outcomes in various ways: violent video game play can arouse aggressive behavior, while prosocial video game exposure increases prosocial behavior (such as helping) and even decreases aggression (Greitemeyer & Mügge, 2014). Most previous studies have focused on the negative effects of video games. Anderson and Bushman proposed the general aggression model (GAM) to explain the impact of violent games on aggressive behaviors (Anderson & Bushman, 2001). The GAM indicates that recent exposure to violent video games can cause short-term aggression by impacting people’s present affect (e.g., anger), cognition (e.g., aggressive scripts), and physiological arousal. People then appraise the situation and decide to act while under the influence of violent video games. When they are dissatisfied with something or someone, they will take impulsive action (similar to their reactions when they are playing violent video games). Based on this model, researchers have found that playing violent video games leads to violent cognition (Gilbert et al., 2013), aggressive affect (Hasan et al., 2012) and aggressive behavior (Adachi & Willoughby, 2011).

However, not all video games contain violent content. Numerous video games contain prosocial content in which players support their partners to achieve game goals in nonviolent ways. Based on the GAM, Buckley and Anderson proposed the general learning model (GLM) to explain the influence of the prosocial content of video games on prosocial behavior (Buckley & Anderson, 2006). This study focuses on the positive effects of the cooperative content of video games on people’s cooperative behaviors according to the GLM.

General learning model

The GLM posits that personal and situational factors interact with the internal state of an individual to trigger changes in prosocial cognition (e.g., positive cooperative attitude), affect (e.g., happiness) and physiological arousal after exposure to prosocial content in video games. Players appraise a situation and decide to act under the influence of video games. When players are satisfied with the results or obtain social support from other players during game play, they prefer to engage in prosocial actions (similar to when they are playing video games). Ultimately, a person may help or cooperate with others after appraisal processes (as shown in Figure 1). Repeated prosocial content in video game exposure contributes to the formation of a prosocial personality (the long-term effects of GLM). Prosocial personality is included in the short-term GLM as a personal factor. Based on the GLM, recent works have shown that brief exposure to the prosocial content of video games can increase players’ prosocial cognition (Greitemeyer & Osswald, 2011), emotion (Saleem et al., 2012) and helping behavior (Velez & Ewoldsen, 2013).

Figure 1.

General learning model: short-term effects of video games (Buckley & Anderson, 2006).

The short-term effects of GLM show that the prosocial content of video games can influence players in three main steps: first, the internal state changes; second, appraisal decision processes are activated; and finally, prosocial action is generated. This study aims to verify the effect of cooperative content in video games on cooperative behavior.

Game mode and cooperative behavior

Recent research has shown that playing cooperative multiplayer (rather than single-player) violent video games involves more cooperative behavior than playing games alone (Greitemeyer et al., 2012). A prisoner’s dilemma-type experiment was conducted to evaluate cooperative behavior to explore the effect of game type (prosocial violent games, antisocial violent games and nonviolent games) on cooperative behavior; the results showed that the short-term influence of game type on cooperative behavior was nonsignificant (Jerabeck & Ferguson, 2013). Inspired by these studies, we speculate that the type of game content (violent or prosocial content) may not be an important factor in players’ behaviors, but the cooperative (multiplayer) game mode may be a key factor in weakening aggressive behavior and generating prosocial behavior in short-term game contact.

According to the GLM, situational factors influence players’ internal states (affect, cognition and physiological arousal) and arouse players’ decision processes, and when players are satisfied with game results or obtain sufficient resource from a video game, they will exhibit prosocial behaviors after game play. Cooperative game mode, as a situational factor, may arouse prosocial cognition, positive affect and physiological arousal. When players get support from ingroup members and cooperate to achieve a game goal, the players obtain sufficient social resource from ingroup members, and thus they will exhibit prosocial behaviors (such as cooperative behaviors, helping behaviors and etc.) towards ingroup members after game play (like when they play a cooperative game together).

Based on previous studies and the GLM, we propose hypothesis 1: a cooperative multiplayer game mode (double-player) may enhance the level of cooperative behavior.

Social value orientation and cooperative behavior

According to the GLM, long-term attitude may contribute to personality to influence subsequent prosocial behaviors. Social value orientation (SVO) is a personality tendency that reflects how people evaluate outcomes for themselves and for others. It reflects people’s willingness to cooperate and their expectations of the behavior of others. SVO divides people into two types: prosocial and proself. Prosocial individuals are willing to cooperate and attempt to maximize collective interests. In contrast, proself individuals demonstrate willingness to primarily pursue self-interest (Bogaert et al., 2008).

In social dilemmas that are used to test the level of cooperative behavior, there are differences between prosocial and proself individuals. For example, prosocial individuals are more likely to cooperate with others (De Kwaadsteniet et al., 2006). Bogaert points out that the reason why prosocial individuals are more likely to cooperate with others is due to their higher expectations of others’ cooperative behavior. Furthermore, prosocial individuals are more likely to be sensitive to prosocial information than are proself individuals. This sensitivity prompts prosocial individuals to discover more prosocial cues to reduce the fear of being betrayed. Cooperative game play provides prosocial individuals with prosocial cues, such as team cohesiveness and trust, and makes them aware of the need to cooperate to achieve game goals. In this way, prosocial individuals have higher expectations of others’ cooperative behavior and may be more likely to cooperate with others. Proself individuals, in contrast, are less sensitive to prosocial information and less easily influenced by the prosocial content of a video game. Furthermore, these individuals assume that uncooperative behavior is a rational choice, and they prefer to maximize their own outcomes by choosing to betray fellow gamers despite the prosocial cues in cooperative video games (Bogaert et al., 2008). In addition, according to the GLM, social value orientation, as a personal trait, can influence prosocial cognition and behavior after exposure to prosocial video game content. Therefore, we propose hypothesis 2: prosocial individuals may show more cooperative behavior than proself individuals after playing video games collaboratively.

Trust affecting cooperative behavior

Trust is essential to establishing and maintaining social relationships. For example, Bosma demonstrates a positive effect of trust on cooperation, but there is no effect of trust on punishment (Bosma, 2019). Therefore, we propose hypothesis 3: trust has positive correlations with cooperative behavior. Trust has a positive effect on cooperation because trust involves expectations of others’ prosocial motives in situations that involve conflicts between one’s own and collective interests (Balliet & Van Lange, 2013), and it encourages mutual cooperative behaviors (Rudnicki et al., 2019). From these insights, based on the GLM, the prosocial content of video games (as found in cooperative game modes) may increase prosocial behaviors, and game task interdependence may increase expectations of others’ cooperative behavior, group members’ perceived responsibility and trust with regard to other group members’ outcomes, contributing to the realization of group success (Velez & Ewoldsen, 2013). Additionally, trust may also increase subsequent cooperative behavior (Sommerfeld et al., 2007). Therefore, we propose hypothesis 4: trust mediates the association between the game mode and cooperative behavior after players collaboratively play video games.

Methods

Participants

The experimenter published recruitment information on the online campus platform, and the participants voluntarily signed up for the experiment (excluding psychology students). The participants were 89 undergraduate and graduate students who provided written informed consent before the experiment and received a reward after the experiment. The sample included 33 men and 56 women aged 17 to 26 years old, with a mean age of 19.92 ± 2.23 years. Furthermore, two experimental assistants (a man and a woman) played as “participants” to complete the experiment with the participants. Every experiment required one assistant and one participant. The two assistants were evenly distributed under each experimental condition according to the participant’s gender.

Materials

Game

Su et al. (Su et al., 2018) and Jin (Jin & Li, 2017) chose League of Legends and War Front, respectively, as game stimuli to examine the impact of cooperative behavior in video games on cooperative behavior. League of Legends is a 5V5 multiplayer online game in which five teammates work together against five other players to achieve the goal of the game. In this game, the interference of competitive elements cannot be controlled in the experimental results. When cooperative behavior is regarded as the dependent variable, competition in games may render the results ambiguous. Moreover, Gentile et al. hold that video games exert an influence on the psychology and behavior of players in five ways: with regard to the amount, content, context, structure and mechanics. The context of the game (the social background) affects players’ actual behaviors; thus, in using League of Legends as the experimental stimulus, the influence of the other eight players (those who are not subjects) on the experimental results cannot be controlled (Gentile, 2011). Therefore, in terms of game selection, this study chose a video game with only cooperative content and no competitive content and with a double-player cooperative behavior mode. Overcooked is a cooperative video game in which one player strives to help another player achieve the game goal; thus, we chose this game as the experimental stimulus in this study.

The content of the game consists of completing dishes ordered by guests through the cooperative behavior of two chefs. The game is played using a keyboard. Each level of the game includes a single-player mode (one player controls two game roles) and a double-player mode (two players control one game role). In this study, we used the 3–2 game level (single-player mode and double-player mode) of Overcooked as the experimental stimulus. The game content of the single-player mode (control group) 3–2 game level was the same as the double-player mode (experimental group) 3–2 game level. The participants reported that they had never played Overcooked before the experiment.

Social value orientation

Social Value Orientation (SVO) is a personality tendency that reflects how people weigh outcomes for themselves and for others (Bogaert et al., 2008). In this study, Murphy’s social value orientation slider scale was used to classify the subjects (Murphy et al., 2011). The SVO task requires participants to give money to themselves and to a stranger. The upper line is the amount of money that the participant gives to him/herself, and the next line is the amount of money given to the stranger. The scale contains six questions, and each question has nine options (as shown in Figure 2). Subjects need to choose one of the nine options for each question (e.g., as shown in the example in Figure 2, choosing the first option means giving oneself 50 CNY and giving the stranger 100 CNY). The calculation formula for SVO is as follows: SVO° = arctan((Y-50)/(X-50)), where $\bar{Y}$ is the mean of the benefits for others, $\bar{X}$ is the mean of the benefits for oneself, and SVO°∈[16.26°, 61.39°]. Participants whose SVO° values are greater than 22.45° are regarded as prosocial, and those whose SVO° values are less than or equal to 22.45° are regarded as proself (Murphy et al., 2011). Participants were told that the SVO results would be used as part of the reward reference.

Figure 2.

SVO slider scale.

Trust game

A trust game was used to measure the degree of trust. In this task, participants needed to complete an investment with another player (experimental assistant); the participant was an investor who had 100,000 CNY principal (hypothetical situation), and another player was a manager (hypothetical situation). The investor had to choose to give 20,000 CNY, 40,000 CNY, 60,000 CNY, 80,000 CNY or 100,000 CNY to the manager (greater investment indicates greater trust). Then, the investment amount tripled; for example, if the investor invested 20,000 CNY with the manager, the manager obtained 60,000 CNY. The investors (participants) were informed of all rules. The results of the trust game determined the final reward the participants received.

Measurement of cooperative behavior

Ewoldsen et al. proved that playing games with others in a cooperative manner could promote subsequent cooperative behaviors (Ewoldsen et al., 2012). However, Jessica et al. found that cooperative games could reduce aggressive behaviors but that they did not significantly improve cooperative behaviors in the real world (Jerabeck & Ferguson, 2013). One possible reason for this inconsistent conclusion may be the difference in the measurement method of cooperative behavior: although both studies chose the prisoner’s dilemma to measure cooperative behavior, the former regarded the frequency of a tit-for-tat strategy as the indicator of cooperative behavior, while the latter regarded the amount of cooperative behavior selected by the subjects as the indicator of cooperative behavior. In fact, using the prisoner’s dilemma paradigm (as shown in Figure 3) to measure cooperative behavior has an obvious defection advantage strategy (when selecting “defect,” players gain 30 or 10, meaning they cannot gain 0; however, when selecting “cooperate,” players gain 20 or 0, meaning 50% gain nothing). In addition, the prisoner’s dilemma is not strictly a risky decision situation (players who choose cooperative behavior may gain a benefit of 20 or 0, while those who choose defection may gain a benefit of 30 or 10; thus, in each choice, the difference is 20). Therefore, participants are more likely to choose “defect” in the prisoner’s dilemma for reasons of risk aversion even though they would like to cooperate.

Figure 3.

Payoff matrices of the prisoner’s dilemma.

The chicken game is also a paradigm for measuring cooperative behavior (as shown in Figure 4). On the one hand, there is no advantage of defection in the chicken game task; on the other hand, the choice of defection is risky (30 or −30), and cooperative behavior is a low-risk choice (10 or −10) compared with the choice of defection. Similar to the prisoner’s dilemma, the chicken game also conforms to social dilemmas in realistic situations (high returns are accompanied by high risks, and low returns are accompanied by low risks). Due to the higher external validity of the chicken game compared with that of the prisoner’s dilemma, in this study, we chose the chicken game to measure cooperative behavior (Su et al., 2018).

Figure 4.

Payoff matrices of the chicken game.

Note. Row chooser’s payoffs are listed first (Su et al., 2018).

There are two players in this task. Each player has two options: cooperative behavior and defection. When both parties choose to cooperate, both parties gain 10 points. If one party cooperates and the other party defects, the partner loses 10 points and the traitor gains 30. If both sides choose to betray, both sides lose 30 points (as shown in Figure 4).

Chicken game process: The experimenter told the participant that he/she would play an online game with another participant (experimental assistant) on two computers in two compartments. The game task was completed using the E-Prime program; the process is shown in Figure 5. The F button indicated cooperative behavior, and the J button indicated defection. The feedback results were fed back after each button press (the participants did not know that the feedback result was a pseudo-randomly generated output with a 50% probability). The participants needed to proceed to the next round of games (10 trials) according to the feedback and their own wishes. Each round of game scores determined the rewards obtained by the participants. The higher the score, the higher the reward. No participants questioned the online game after the experiment was completed (in another compartment, there were two experimental assistants; one played the “participant,” and the other played the “experimenter.” True participants believed that the other player was also a participant).

Figure 5.

Chicken game task.

The participants’ rewards (10–20 CNY and 1–10 CNY gifts) depended on the results of SVO, trust, and the chicken game task.

Procedures

Experimental design

In this study, a 2 (prosocial/proself) × 2 (single-player/double-player) experimental design was used to measure the influence of SVO and the game mode on cooperative behavior (the frequency of choosing cooperative behavior). The participants’ perceived familiarity and frustration during the game were used as covariates. An a priori power analysis using G*Power was performed to calculate the proper number of participants. The total sample size based on the a priori power analysis was 73 (effect size f = 0.4, α err prob = 0.05, Power (1-β err prob) = 0.8, Numerator df = 3, Number of groups = 4, Number of covariates = 2). There were 89 participants (> 73); this number was sufficient.

Experimental process

Before the experiment, the participants completed the basic information questionnaire (e.g., gender, age, year at university, major, number of years playing games, SVO, whether they had played Overcooked games). Then, they were introduced to the other participant in the experiment (in reality, the lab assistant). The subjects were randomly assigned to either a single-player or double-player group.

With regard to the formal experiment, the participants had never played Overcooked before the experiment. Thus, to avoid misoperation, the experimenter briefly taught the participants the basic operation of the game. Then, the participants played the game alone in either the single-player mode or the double-player mode (a participant assigned to the double-player mode played the game with a lab assistant in the same room). Each level of the game required four minutes to complete. Then, these two people were divided into different rooms to complete the following tasks. After the game was over, trust was measured using the trust game. Finally, cooperative behavior was measured using the chicken game.

Data analysis

Using SPSS 22.0, we conducted MANOVA to explore the effect of SVO and the game context on cooperative behaviors. SPSS 22.0, LSD was applied to perform the post hoc tests.

In addition, PROCESS of SPSS was used to test the mediating effect of trust on the association between the game mode and cooperative behavior. The bootstrap estimation procedure (with a sample of 5000) was used to test the significance of the mediation effect. If the 95% confidence intervals (CIs) did not include zero, then the significance of the mediating effect was accepted (Wang et al., 2020).

Results

An independent-sample t test was used to test the effect of lab assistants on cooperative behavior and trust. The independent variable was two lab assistant groups, and the dependent variables were cooperative behavior (t (87) = −0.47, p > 0.05) and trust (t (87)=0.59, p > 0.05). The results showed that different lab assistants had no significant effect on cooperative behavior and trust.

The influence of SVO and the game mode on cooperative behavior

The MANOVA results show that the main effect of SVO on cooperative behavior was significant, F(1,83) = 4.20, p < 0.05, η_p² = 0.05. Prosocial individuals (M = 5.93, SD = 2.51) had higher cooperative behavior than proself individuals (M = 4.94, SD = 1.92). The first result shows that prosocial individuals exhibit more cooperative behavior than proself individuals. The main effect of the game mode on cooperative behavior was significant, F(1,83) = 25.21, p < 0.001, η_p² = 0.23. Cooperative behavior under the single-player mode (M = 3.77, SD = 1.42) was lower than that under the double-player mode (M = 7.28, SD = 1.86). Therefore, we can draw the second conclusion: playing in a double-player mode (collaborative game play) can increase subsequent cooperative behavior. SVO and the game mode had a significant interaction effect on cooperative behavior, F(1,83) = 14.19, p < 0.001, η_p² = 0.15. A simple effects analysis was needed.

The simple effects analysis showed that for proself individuals, the difference in cooperative behavior between the single-player C1 (M = 4.29, SD = 1.70) and the double-player C2 (M = 5.40, SD = 2.01) game mode was not significant, F(1, 83) = 0.90, p > 0.05. However, the cooperative behavior of prosocial individuals C1 (M = 3.66, SD = 1.36) was significantly lower than that of C2 (M = 7.75, SD = 1.55), F(1, 83) = 105.80, p < 0.001. After playing in the single-player mode, the cooperative behavior of proself individuals (M = 4.29, SD = 1.70) and prosocial individuals (M = 3.66, SD = 1.36) was not significantly different, F(1, 83) = 1.32, p > 0.05. After playing in the double-player mode, the cooperative behavior of proself individuals (M = 5.40, SD = 2.01) was significantly lower than that of prosocial individuals (M = 7.75, SD = 1.55), F(1, 83) = 20.65, p < 0.001. This result shows that playing video games collaboratively can increase prosocial individuals’ cooperative behavior but cannot increase proself individuals’ cooperative behavior.

The relationship between cooperative behavior, game mode, and trust

Cooperative behavior had a positive correlation with trust (r = 0.58, p < 0.01).

As shown in Figure 6, trust partially mediated the association between the game mode and cooperative behavior. The game mode could significantly predict trust (a = 2.2626, R²= 0.3353, t = 6.6253, p < 0.001). Additionally, trust could significantly predict cooperative behavior (b = 0.3006, R² = 0.5568, t = 2.7357, p < 0.01). Furthermore, the game mode could significantly predict cooperative behavior (c′ = 2.8305, t = 6.5920, p < 0.001). In the bootstrap procedure, the direct effect of the game mode on cooperative behavior showed that the lower-limit confidence interval (LLCI) was 1.9769 and that the upper-limit confidence interval (ULCI) was 3.6841, meaning that the direct effect was significant (it did not include zero). In the bootstrap procedure, the indirect effect of the game mode on cooperative behavior showed that the LLCI was 0.1436 and that the ULCI was 1.3151, meaning that the indirect effect was significant (it did not include zero). R² _med was used to reflect effect size (Preacher & Kelley, 2011); R² _med = 29.44%, meaning that 29.44% of the variance in cooperative behavior could be explained by game mode and trust, with a 95% CI [0.1694, 0.4140].

Figure 6.

Mediating effects of trust between the game mode and cooperative behavior.

Discussion

This study shows that the multiplayer game context can promote cooperative behavior in the real world, which is consistent with the results of Velez (Velez & Ewoldsen, 2013; Velez, 2015; Velez, 2018). Velez found that the theory of Bounded Generalized Reciprocity (BGR) could explain prosocial behaviors in ingroup members after cooperative video game play: players in the double-player game mode were more inclined to cooperate with ingroup members because of their expectations of others to reciprocate behaviors (Velez, 2015). In this experiment, the participants in the double game mode expected ingroup members to reciprocate behaviors in the chicken game, so they were more likely to cooperate in the chicken game first. Social interdependence theory can be used as a supplement to explain this phenomenon. Social interdependence appears when the outcomes of individuals are affected by their own and others’ behaviors (Johnson & Johnson, 2009). There are two types of social interdependence: positive (when the actions of individuals promote the achievement of joint goals) and negative (when the actions of individuals obstruct the achievement of joint goals). In the double-player game mode, achieving the game goal depends on positive coordination (Wilson et al., 2006). Thus, positive interdependence is aroused in the double game mode, and it promotes participants to cooperate with ingroup members to achieve a win-win situation. In addition, according to the short-term effect of the GLM, individuals’ internal cognition, affect and physiological arousal status change when they cooperatively play video games. When the game results are output, individuals determine whether the results are satisfying and important. After obtaining positive results (like achieving game success through cooperation), participants learn to cooperate with others in video games and subsequent tasks, which allows win-win outcomes. This is the total short-term learning process of video games (Buckley & Anderson, 2006).

This study also indicates that prosocial and proself individuals have no differences in cooperative behavior in the single-player game mode but that prosocial individuals show more cooperative behavior than proself individuals in the double-player game mode. Cooperative game play can significantly increase prosocial individuals’ cooperative behavior but cannot significantly increase proself individuals’ cooperative behavior. These results are consistent with the findings of Bogaert (Bogaert et al., 2008). Bogaert noted that due to their willingness to cooperate, prosocial individuals were likely to be sensitive to prosocial information because this sensitivity verified the positive expectation that their cooperative behavior would be reciprocated and would reduce the fear of being betrayed (Bogaert et al., 2008). In this experiment, short-term cooperative game play aroused cooperative willingness and promoted cooperative behavior more easily for proself individuals. In contrast, due to their willingness to pursue self-interest, proself individuals need explicit incentives to align the aim of pursuing their own interest with the aim of cooperating with the collective. Short-term prosocial game stimuli can be too weak for proself individuals to pursue cooperative behavior. In addition, only prosocial individuals are inclined to regard the game as involving coordination, in which the win-win outcome is their preferred choice; thus, they are more likely to choose cooperative behavior during the chicken game task. Given the same matrix, proself individuals prefer the outcome that is the opposite to that of their partner to obtain higher scores in each round of the chicken game task. Maximizing their own outcomes by not cooperating is the preference of proself individuals; thus, they choose cooperative behavior less often than do prosocial individuals (Simpson, 2004).

Furthermore, this study also indicates that trust partially mediates the association between the game mode and cooperative behavior, which is consistent with the study by Chang (Chang, 2014). Chang revealed that trust contributed to online cooperative learning environments. Lui also noted that trust played a key role in leading to cooperative behavior between groups and that it was conducive to the group’s performance (Lui et al., 2009). In this study, game play interdependence aroused players’ team cohesiveness and made players aware of the need to trust teammates, coordinate their efforts and cooperate to achieve game goals. Therefore, the cooperative components of the double-player mode in video games contribute to trust in teammates, and trust also leads to cooperative behavior.

The short-term effects of GLM are partially demonstrated in this study: the cooperative game mode in video games can promote cooperative behaviors. Additionally, prosocial individuals have more cooperative behaviors than proself individuals after cooperative game play, and the cooperative components of video games contribute to trust in teammates, which also leads to cooperative behavior. Additional longitudinal experiments are needed to better understand the long-term effects of GLM to illustrate the long-term positive effect of cooperative content in video games. For certain violent video games, Jerabeck and Ferguson (2013) found that violent content in video games had no influence on pro-social behavior, but whether games were violent or not, playing cooperatively was associated with less aggressive behavior. We suggest that the cooperative game mode could weaken the negative effect of violent video games; however, the mechanisms of this process are still not clear. Therefore, further studies on these mechanisms are needed to deeply understand the positive effects of different types of video game.

Footnotes

Article Notes

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