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Design of an in-game economic system based on virtual currency and its impact on player behavior

  
Mar 21, 2025

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Introduction

The in-game economic system is an economic system built in a virtual society. The game also has a value system of inputs and outputs.

The in-game economic system can be divided into four parts: production, accumulation, exchange and consumption, which can be explained by relevant concepts in political science. Production, whose elements are mainly two kinds of labor and labor tools [1-2]. We can think that all the activities that exist for a certain purpose are labor, such as leveling, killing monsters, collecting, etc.; while the tools of labor, is the labor process, the player has the ability to labor average labor time determines the value of the production, and the tools of labor determines the efficiency of the individual production, such as the player’s level, equipment, skills, magic and so on. Accumulation, mainly the accumulation of labor tools, such as levels, skills, magic, equipment, materials, props, etc. [3]. Exchange, in massively multiplayer online role-playing games, the biggest feature is player interaction, so exchange becomes a key factor in human interaction [4]. Currency plays the role of equivalence in exchange, in the case of better control of the number of game currency, the amount of currency owned by the player can generally determine how much value the player has, how strong the purchasing power. Consumption, the most important part of the online game economic system, can determine the frequency of exchange, such as World of Warcraft players to buy fireworks, dresses, etc. [5-7]. Accumulation and exchange, which are players’ own behaviors, do not involve interaction with the economic system. Production and consumption, on the other hand, correspond to 2 important value flow channels in the economic system.

However, with the development of the game industry, virtual economy has become an important part of game design. Virtual economy design can not only increase the fun of the game, but also increase the participation of players, thus enhancing the value of the game [8-10].

This study analyzes the effects of game accounts, virtual currency, and game props on the determination of game value.It also designs an economic system for games based on PIPE modeling. Through the introduction of virtual currency elements such as “gold”, “yuanbao” and “chest” in the economic system, we put them into five games to assess the design rationality and analyze the players’ props trading behavior and the online behavior of the economic system. Players’ online behavior in trading props and the economic system is analyzed. On this basis, the regression model is combined to predict other behaviors of players in the game.

Overview

Virtual currencies have been used in all kinds of games for a long time, but the acquisition of virtual currencies is usually a reward for winning the game process, but the vast majority of them need to be purchased in real real currency, and players will be hesitant to do so. However, the literature [11] introduces both virtual currency and real money. Free game players are willing to pay, but the transaction situation is different due to the presence of different exchange resources.In this regard, game developers can refer to the ratio of resource exchange to design the focus of the economic system in a targeted way. Literature [12] mentioned in the study according to the player in the game time to buy or consume virtual currency for the module design of the virtual sales strategy, the supplier can be based on the player’s game time and the ability to buy real-time adjustment of the strategy, this strategy can help to provide reference for the design of the economic system within the game.

Literature [13] also mentions that selling virtual currency can help in-game vendors place advertisements to increase revenue, and can also reduce player addiction. Literature [14] mentions that in social casino games, players can earn virtual currencies by winning the game, or they can make purchases using real money to continue the gaming experience, with the risk of increasing player addiction. Cryptocurrency is a type of virtual currency [15]. Literature [16] mentions that game props can be exchanged for cryptocurrencies and then regular currencies in Terafern crypto games, which is a resource exchange that players are happy to see. However, literature [17] points out that virtual currencies are largely monitored by economic laws to prevent people from using them for money laundering, whereas cryptocurrencies use cryptographic principles to ensure the security of currency transactions, which also makes anti-money laundering rules challenging. In addition, cryptocurrencies have security threats, crash risk of the system, impact on the real currency, gold rush risk, fluctuation in the value of virtual currencies, unknown risk of the player’s identity, and black market of cryptocurrencies [18].

The impact of virtual currencies on in-game economic system design and player behavior does not stop there. Economic system design involves laws, regulations, and ethical rules, while players are also responsible for their psychological and physiological health, as well as engaging in the most typical addictive behaviors.

Implications for the determination of the value of games based on virtual currencies

Virtual property in online games can be categorised into three types: first, the game accounts owned by online game consumers. The second is the general equivalents capable of payment transactions in online games, i.e. the virtual currency in the game. The third aspect is the game props that fulfill the game requirements of online game consumers.

Game accounts

Online game, also known as online game, refers to a form of game in which the game process requires connecting the game operator’s server and the user’s computer through the public Internet, and utilizing the game client software for information interaction. The game account takes the account number and password as the external manifestation form, and the storage space of the network server as the carrier, which connects the real space of human beings with the virtual space of the game.

Game account as a game player’s personal play experience of the whole collection, each game player to its investment of time, energy, money is different, the role of the acquisition of props are not. This indicates that even if there exists a market for trading game accounts, the trading prices of other game accounts in that market cannot be used as a direct reference for determining value.The price of a game account in a transaction is greatly affected by the subjective factors of both the seller and buyer. If the perpetrator sells the victim’s game account to sell the stolen goods, the amount of the stolen goods is likely to be very different from the true value of the game account, and it is not convenient to use it as a criterion for determining the amount of the crime.

Virtual currency

Virtual currency in online games [19-20] is an electronic exchange instrument in the form of an electromagnetic record of existence issued by the game operator and expressed in digital units. Users can purchase or exchange these tokens for legal tender at a specific rate and store them within the servers provided by the game operator.

These virtual currencies can be exchanged for online game services provided by the enterprise, usually in the form of prepaid recharge cards, points or amounts, and do not contain items such as props obtained through game activities, and the virtual currencies can also be exchanged for game props, game coins or other value-added services.

Game props

Game props, or game items, are a collective term for various virtual items in games. Game props are generally of different types, such as equipment-type, consumable-type, quest-type, material-type, and so on. There are various ways to obtain them, such as dropping them by fighting monsters, completing game tasks, purchasing or exchanging them through NPC merchants in the game, purchasing them directly in game malls using virtual currencies, and trading or auctioning them with other players within the game. The value of game props is greatly affected by many factors. For example, the network operator’s adjustments and modifications to the game, the increase or decrease in the value of specific props or changes in the probability of dropping will affect the value of the props in the players. Game props are only valuable to players who play the same online game, and among such players, a stable trading price system is often formed, and players trade game props with each other through official or third-party intermediary platforms, which is no different from online shopping for real goods.

In-game economic system modeling design
Virtual currency elements of the economic system

The economic system constructed in this paper is a typical large-scale economic system in which in-game and rechargeable coins circulate. Here is the introduction of the basic concept of economic system elements in the game.

Gold: the game currency circulating in the game, the most important way is still from the daily quests to obtain, day after day to form the accumulation and circulation, so as to constitute the basic currency transactions.

Yuanbao: the rechargeable coins in the game, only paid players can get Yuanbao after recharging and exchanging, which itself cannot circulate, but can get different materials by purchasing different categories of mall items to achieve the expectation of final consumption.

Boxes: Various random props in the mall that require Yuanbao to be purchased and opened can be uniformly referred to as boxes. Boxes are the guarantee of Yuanbao’s consumption diversity. More than 70% of the consumption items are produced through the box output.

Materials: The tradable items produced in the chests can be uniformly called materials. Players buy and sell materials using gold coins to fulfill their needs, which is an important link in the circulation process of the economic system.

Treasure Pavilion: the official trading platform, players can buy and sell materials, gold coins and even the account itself, due to the official technical support, credibility and convenience is guaranteed, is the most core use of the most widely used circulation platform.

Equipment Synthesis: Through equipment synthesis, players consume various items and gold coins to obtain better equipment, thus enhancing their own attributes.

System Recycling: In the process of the game, many operations need to pay gold coins directly to the system at NPCs, and these gold coins will not enter the circulation again, and will be directly recycled by the system to disappear, which is the most important and direct means of controlling inflation.

Non-growth consumption: After the paid player spends, there is no enhancement of attributes, which becomes non-growth consumption. This can be roughly categorized as ornamental consumption and ostentatious consumption.

System modeling
Analysis of the correlation of economic elements
Gold output input

The output of gold coins in the game mainly comes from three major sources:

Figure 1 shows the output model of gold coins in the game. Daily treasure quests are stable drops that can be done repeatedly once a day, and the most important source of systematic gold output still comes from this segment, and the amount of output changes according to one’s level. Next are the regular plot quests and the main line iterations introduced with each version update, which will give players who complete the quests generous rewards, the amount of which depends on the length of the quest line and the value of the single reward. Finally, there are monster drops, which are the probability of which most players don’t have access to actual data, and which are among the smallest in terms of the game’s performance.

Figure 1.

Model of gold coin production in the game

Yuanbao recharge input and consumption intention

The game Yuanbao recharge consumption model is shown in Figure 2. Yuanbao recharge mainly comes from online payment, and the exchange ratio is kept constant at 1RMB equal to 10 Yuanbao without considering the purchase discount. It is worth noting that once RMB is recharged into the game system, there is no refund or transfer of Yuanbao, and of course Yuanbao will not disappear or decrease with time.

Figure 2.

Consumption model of ingot after recharging

Gold Coin System Recovery

Every player, regardless of participating in PVP or PVE activities, will suffer a certain degree of damage to their equipment, and then they need to pay a certain amount of gold coins to the system for repair. The purpose of this type of corresponding gold coin recovery in the case of daily gold coin placement is to maintain the stable operation of the entire game economic system. Figure 3 shows the gold coin recovery model in the game.

Figure 3.

Model of gold recovery in the game

Reinforcement output:

Reinforcement output refers to the player’s consumption of treasure and gold, which is mostly used to enhance their own equipment and attributes. This is also a relatively large part of the game’s player consumption.

Show-off and ornamental output:

In this paper, taking into account the game’s actual player demand, the main reason for the distinction is that a large number of players in the game will choose to buy excessive amounts of mounts and fashions, the purchase of which can last for more than 3 years, which exceeds the original role they should be used as ornamental, in fact, is a kind of collection and show-off mentality of the behavior of the outward appearance.

Furnace Synthesis:

Refining Furnace Synthesis is the current game’s collection of several functions such as acquiring, upgrading, resetting, etc., and is also the final destination of most materials. Among them, skill points are a separate numerical system, and there is no overlap with the economic system. Corresponding to the prestige props is relatively complex, the prestige itself is obtained from the yuan treasure consumption, can only be used through the exchange into the corresponding props, but some of these props can be traded the rest can only be held by the player himself.

Economic system model based on PIPE modeling

The PIPE-based economic system model is shown in Figure 4.

Figure 4.

Economic system model based on Petri Net

Tables 1 and 2 show the detailed library and change meanings, respectively. The meaning of P0-P21 is shown in Table 1:

The meaning of the economic system model library

Library Meaning
P0 Gold coin
P1 Tradable material
P2 The utility of the yuan bao consumption
P3 The treasure of the converted post
P4 The production intention of the military style
P5 The desire of the ornamental yuan bao
P6 Visual system output
P7 The collection of the event rewards items
P8 Daily task treasures fall in collection
P9 The system hits the monster’s falling collection
P10 Consumer intention of consumption
P11 Satisfy the synthesis conditions of the furnace
P12 System gold recovery
P13 The gold coins required for daily sustainability
P14 The gold coins required to learn and wash out skills
P15 Gold coins required for maintenance and maintenance
P16 The gold coins required to maintain the consumption
P17 Instant direct money consumption
P18 Equipment and other goods
P19 Conspicuous system output
P20 Enhanced system output
P21 The rmb is reset to the amount of the account

The meaning of T0-T28 is shown in Table 2:

The economic system model changes the meaning table

Transform Meaning
T0 Treasure into a coin of gold
T1 The plot rewards gold coins
T2 The monster fell and sold the gold coins
T3 Sell material for gold
T4 Use gold coins for change
T5 Obtain tradable material after utility consumption
T6 Utility consumer purchase treasure box
T7 The premium yuan bao selects the utilitarian consumption
T8 The premium yuan bao chooses consumable consumption
T9 The premium yuan bao chooses ornamental consumption
T10 Optional equipment maintenance
T11 The selection of optional forces is maintained in daily maintenance
T12 Choose the gold coins that are maintained daily
T13 Choose the gold coins to learn and wash
T14 Equipment maintenance
T15 Power maintenance
T16 Learning skills or washing
T17 Make a composition of gold coins
T18 The consumption materials are synthesized
T19 Yuan bao consignment for gold coins
T20 Consumption of the content of consumption
T21 Conspicuous consumption of conspicuous yuan in the expendable limit
T22 We will carry out the consumption of enhanced yuan
T23 Use synthetic equipment and other items to strengthen
T24 The furnace is synthesized and obtained
T25 The smelting furnace synthetic consumption gold gold for recycling
T26 Open the treasure box for gold
T27 To carry out the consumption of ornamental yuan bao
T28 Convert the RMB in proportion to yuan bao

Questionnaire-based research on the recognition of economic systems
Questionnaire design

This study develops an offline research experiment to assess the recognition of the economic system designed in this paper, based on questionnaires from other game studies.The questionnaire contains the following six main dimensions: currency stability, price reasonableness, distribution balance, game experience, game fairness, and consumption willingness. Each dimension has five survey questions, which are in the form of a five-level Likert scale, and players score each question item according to their own situation, in which total disapproval represents one point, comparative disapproval represents two points, general represents three points, comparative approval represents four points, and total approval represents five points.

Distribution and return of questionnaires

A total of 100 questionnaires were distributed in this study and 100 were recovered with a recovery rate of 100%. The basic situation of questionnaire recovery is shown in Table 3.

Questionnaire recovery basic condition

Sample condition Options Number
Play games YES 96
NO 4
Total 100
College student YES 83
NO 17
Total 100
Completely inconsistent sample 3
Fully matched sample 97
Total 100
Reliability tests

Reliability is a measurement concept that centers on testing the internal consistency of a scale. Only by passing the reliability test can we demonstrate that the data recovered from the questionnaire are true and reliable. This study mainly uses the calculation of the Alpha of the scale to test the internal consistency of the scale, in general, the Alpha coefficient is greater than 0.9, which indicates that the scale has a high degree of internal consistency, when the Alpha coefficient is between 0.7-0.9, it indicates that the internal consistency of the scale is relatively good, when the Alpha coefficient is lower than 0.7, it indicates that the scale’s individual items have a high degree of inconsistency, the Questionnaire data point reliability is low and questionnaire data are unreliable. The results of the reliability analysis for each dimension of the scale questions are shown in Table 4.

The overall Alpha coefficient of the questionnaire scale questions is between 0.952 and 0.996, and this study considers that the data reliability of the questionnaire scale questions in this study is high, and the collected data are real and reliable, and can be analyzed in the next step.

Analysis of the reliability analysis of each dimension of scale subject

Scale dimension Issue number Average Alpha coefficient
Currency stability 1-5 0.963
Rationality of price 6-10 0.952
Balance of distribution 11-15 0.956
Game experiability 16-20 0.996
Fairness of game 21-25 0.978
Consumption willingness 26-30 0.983
Analysis of questionnaire results

The results of the questionnaire survey are shown in Figure 5. From the figure, it can be seen that players have a high degree of recognition of the game economic system designed in this paper, and the overall average recognition is 4.389. Specifically, the ratings of the stability of the currency, the reasonableness of the price, the balance of distribution, the game experience, the game fairness, and the degree of willingness to consume are 4.34, 4.48, 4.09, 4.66, 4.22, and 4.54 respectively, among which the player experience of the game has the highest rating, indicating that the game economy system designed in this paper can simulate real-world economic activities and provide players with space for economic decision-making and strategy planning.

Figure 5.

The results of the recognition questionnaire survey

Analysis of player behavior based on different game economic systems
Analysis of Players’ Prop Trading Behavior

This section collects data on player prop transactions in five game economic systems and processes and analyzes the transaction data. The transaction quantity and transaction amount information of buyers (who have at least one purchase record) and sellers (who have at least one sale record) in each game are counted. The virtual currencies consumed or earned are loaded and exchanged into RMB according to the ratio of each game platform, and then compared and analyzed, and their respective box plots are drawn accordingly. Figures 6 and 7 show the results of the distribution of the number of prop transactions, the amount spent on buying props, and the amount of income from selling props in different game economic systems, respectively.

Figure 6.

The number of trading transactions in different game economy systems

Figure 7.

The amount of money purchased and the amount of money sold

Combined with the two figures, most of the buyers in the five games purchased props in quantities of no more than 40, and the virtual currency spent on purchases was converted to RMB less than 800 yuan. These buyers should represent the majority of users in the games, who only pay a small amount of money to try out the gameplay. The number of props sold by sellers is overall higher than the number of props purchased by buyers, and the amount of sales revenue is higher than the amount of money spent by buyers, suggesting that ordinary small players mainly buy props from big players.

In addition, the mean of the number of props bought by buyers and the amount spent by buyers in the five games are significantly higher than the median, indicating that some big players buy a lot of props or spend a very high amount of money, indirectly reflecting the existence of a large gap between rich and poor buyers. The average number of props sold and sales revenue of sellers are also significantly higher than the median, indicating that a small number of sellers dominate the market and capture most of the revenues in the game while selling a large number of props.

Percentage of online hours for economic system games

In addition, in this section, we collect the online time behavior of the above five games, with different virtual currency players, in the game economic system to analyze the degree of relationship between virtual currency and the in-game economic system. Similarly, due to the differences in the value of virtual currencies in different games, this section also measures the in-game virtual currencies by converting them into RMB. The percentage of time spent in the economic system by players with different amounts of virtual value in the game is represented in Figure 8.

Figure 8.

The time ratio of the economic system

The data in the figure shows that for the five games, as the amount of virtual currency value increases, the time spent by players in the in-game economic system gradually increases. When the player does not have virtual currency, the percentage of time in the economic system is close to 0. It is logical that when the virtual currency is 0, the player is willing to spend more time fighting monsters or obtaining in-game virtual currency in the form of completing quests. When players have enough or more virtual currency, they have more choices in the in-game economic system and therefore spend more time online. Virtual currency is the currency of exchange in the in-game economic system, and the rational design of the system encourages players to spend more time trading virtual currency.

Multiple linear regression analysis based on player behavior

For the study of a regression model with one dependent variable and two or more independent variables, it is called multiple regression. According to the research content of this paper, multiple regression analysis is applied. Taking into account the convenience of model calculation and other factors, in practice, the linear model is usually preferred for fitting, and when encountering a nonlinear model, a certain method can also be used to convert it to a linear model. Therefore, in this paper, when performing multiple regression analysis, the linear model is selected for fitting.The application steps of multiple linear regression models [21-22] mainly include:

Constructing regression equations

Let y be an observable random variable that receives the effect of p non-random factor xI,x2,⋯,xp and random factor ε and y has a linear relationship with xl,x2,⋯,xp. The multiple regression linear equation is given by: y=β0+βlxl+...+βpxp+ε \[y\;=\;{{\beta }_{0}}\;+\;{{\beta }_{l}}{{x}_{l}}\;+\;...\;+\;{{\beta }_{p}}{{x}_{p}}\;+\;\varepsilon \] where y is the dependent variable. xi(i = 1,2,⋯,p) is the independent variable. βi(i = 0,1,2,⋯,p) is the regression coefficient, which reflects a measure of the linear effect of the ith independent variable xi on the dependent variable y. ε represents the error between the regression value and the measured value, which is usually assumed ε~N(0,σ2).

Applying Least Squares to Estimate Unknown Parameters

With n independent observations of y and xi(i = I,2,⋯,p), n sets of sample data (xi1,xi2,⋯,xip; yi)(i = I,2,⋯,n) are obtained: {y1=β0+β1x11+β2x12+...+βpx1p+ε1y2=β0+β1x21+β2x22+...+βpx2p+ε2yn=β0+β1xn1+β2xn2+...+βpxnp+εn \[\left\{ \begin{matrix} {{y}_{1}}={{\beta }_{0}}+{{\beta }_{1}}{{x}_{11}}+{{\beta }_{2}}{{x}_{12}}+...+{{\beta }_{p}}{{x}_{1p}}+{{\varepsilon }_{1}} \\ {{y}_{2}}={{\beta }_{0}}+{{\beta }_{1}}{{x}_{21}}+{{\beta }_{2}}{{x}_{22}}+...+{{\beta }_{p}}{{x}_{2p}}+{{\varepsilon }_{2}} \\ \vdots \\ {{y}_{n}}={{\beta }_{0}}+{{\beta }_{1}}{{x}_{n1}}+{{\beta }_{2}}{{x}_{n2}}+...+{{\beta }_{p}}{{x}_{np}}+{{\varepsilon }_{n}} \\ \end{matrix} \right.\] where εl,ε2,⋯,εn are independent of each other and all obey N(0,σ2), the above equation can be expressed in matrix form: Y=Xβ+ε \[Y=X\beta +\varepsilon \] where Y = (yl,y2,⋯,yn)T,β = (β0,β1,β2,⋯,βp)T ,ε = (εl,ε2,⋯,εn)T, ε ~ Nn(0,σ2In), In are unit matrices of order n: X=[1x11x12...x1p1x21x22...x2p1xn1xn2...xnp] \[X=\left[ \begin{matrix} 1 & {{x}_{11}} & {{x}_{12}} & ... & {{x}_{1p}} \\ 1 & {{x}_{21}} & {{x}_{22}} & ... & {{x}_{2p}} \\ {} & {} & \vdots & {} & {} \\ 1 & {{x}_{n1}} & {{x}_{n2}} & ... & {{x}_{np}} \\ \end{matrix} \right]\]

Applying the least-squares method, the least-squares estimate of b1,b2,…,bp is calculated to be β0,β1,β2,…,βbp, respectively, and this multiple linear regression equation is: y=b0+blxl+...+bpxp \[y\;=\;{{b}_{0}}\;+\;{{b}_{l}}{{x}_{l}}\;+\;...\;+\;{{b}_{p}}{{x}_{p}}\]

Hypothesis testing

Multiple linear regression model is only a hypothesis, in the actual problem, to determine whether the model has a good fit with the actual data, the significance of the linear relationship of the model, etc., but also need to be tested through the combing statistics to decide whether the model is scientifically applicable. The commonly used test is the F-test:

The test of significance of the regression equation is designed to make a judgment as to whether the linear relationship between y and xl,x2,⋯,xp in the model holds significantly in the aggregate.

The original hypothesis is H0 : βI = β2 = ⋯ = βp = 0 The alternative hypothesis is Hi : βj Not all 0 If the original hypothesis is valid, there is no significant linear relationship between the dependent and independent variables in the model and the statistic F is constructed to test it: F=1n(yiy¯i)2/p1n(yiy^i)2/(np1)~F(p,np1) \[F=\frac{\sum\limits_{1}^{n}{{{({{y}_{i}}-{{{\bar{y}}}_{i}})}^{2}}}/p}{\sum\limits_{1}^{n}{{{({{y}_{i}}-{{{\hat{y}}}_{i}})}^{2}}}\;/(n-p-1)}\tilde{\ }F(p,n-p-1)\]

Given a significance level of α , check the table to get Fα(p,npI). The test rule is:

If FFα(p,np–1), the original hypothesis is accepted and the regression model cannot be used for prediction.

If F > Fα(p,npl), the original hypothesis is rejected, indicating that the regression model is significant and can be used for predictive analysis.

Regression Prediction of Economic Systems and Player Game Behavior

The in-game economic system and player game behavior (social behavior, competitive behavior, immersion behavior, and consumption behavior) were analyzed using regression analysis.Table 5 displays the results of the regression analysis of player game behavior based on the economic system.

According to the data in the table, it can be seen that Currency stability, Rationality of price, Balance of distribution, Game experiability, and Fairness of game provided by the system in this paper have a positive influence on players’ game behavior. The regression coefficients for players’ social behavior, competitive behavior, immersion behavior, and consumption behavior range between 0.106 and 0.383, and all of them are significantly different.Among them, the influence on consumption behavior is the largest, with regression coefficients range from 0.219 to 0.383, which passes the significance test at the 0.001 level. That is, if the factors of this paper’s system are increased by one unit, the player’s consumption behavior can be increased accordingly at the 0.001 level by 0.219~0.383. This indicates that the more comprehensive this paper’s system is, the more the player’s game consumption behavior will increase.Driven by the economic system, players want to have fun in the game but also obtain better props, equipment, clothing, etc. in the game, they need to pay for it.

The game behavior regression prediction based on the economic system

Variable Game behavior
Social behavior Competitive behavior Immersive behavior Consumer behavior
Currency stability 0.193** 0.231** 0.191** 0.315***
Rationality of price 0.141** 0.163** 0.159* 0.383***
Balance of distribution 0.126* 0.216** 0.112* 0.219***
Game experiability 0.188** 0.172** 0.106* 0.347***
Fairness of game 0.178** 0.167** 0.134** 0.377***
R2 0.197 0.213 0.177 0.226
F 19.623 17.431 15.492 16.458

*, **, *** indicate p significant at 0.5, 0.1, 0.01 level respectively

Conclusion

This paper constructs an in-game economic system and analyzes the correlation between each virtual currency element in the system. Through the questionnaire, the stability of the currency, the reasonableness of the price, the distribution balance, the game experience, the fairness of the game, and the degree of players’ willingness to consume in the system of this paper are evaluated. Combined with multiple linear regression equations, the game behavior of players is analyzed.

1) The overall average recognition degree of 100 players to the game economic system in this paper is 4.389, which is “relatively recognized”.

2) In this system, ordinary small players are more willing to spend virtual currency to buy game props from big players.

3) Players with higher value of virtual currency spend more time in the economic system of this paper. When the value of virtual currency is 500 yuan, the proportion of online time ranges from 7.89% to 16.08%.

4) The nature system can significantly improve players’ social behavior, competitive behavior, immersion behavior, and consumption behavior.

Language:
English