Virtual Items Pricing in Online Games

Transcription

1 Virtual Items Pricing in Online Games Ernie G.S. Teo Division of Economics, anyang Technological University Chanbora Ek Division of Economics, anyang Technological University April 7, 009 Abstract The rapid growth of broadband internet access around the world has lead to the emergence of Multiplayer Online Games (MPOGs). MPOGs are computer games where players interact socially online. Most rms providing these games traditionally followed a two-part tari pricing model, this is due to the large network externalities involved. Recently, we observed many new games abandoning this traditional model in favour of the "free to play" model and selling optional virtual items. Virtual items are add on items which gamers can buy to enhance their gaming experience. The purchase of virtual items are not compulsory, gamers can in fact play the game for free without purchasing any items. In this paper, we examine the virtual items pricing model with an economic theory framework. We found that the opportunity costs for gamers must be su ciently low for such a model to be pro table to the rm. As long as opportunity cost is low, there will exist gamers who will buy items and gamers who just play the game without any purchase. Keywords: Multiplayer Online Games, Virtual Items, Pricing, etwork Externalities JEL Codes: D40, L11, L86 Corresponding Author. Tel.: Address: Division of Economics, anyang Technological University, anyang Avenue, Singapore address: gsteo@ntu.edu.sg 1

2 1 Introduction 1.1 Background With the rapid growth of the availability of large internet bandwidth, computer games where many players interact online became more feasible. Many large computer game rms jumped on this bandwagon in the late 1990s with Ultima Online being one of the pioneers of the Multiplayer Online Games (MPOGs) industry. Players of MPOGs interact socially online, the enjoyment of such interactions depends on the amount of other people playing the game. These social interactions can be forming teams to ght against enemies in fantasy type games or simply just going about daily activities in virtual world such as those found in the game "Second Life". The MPOGs industry exhibit many features which are of interest to the analysis of economic pricing models. As pointed out in Meagher and Teo (005), these features include creative destruction (games get replaced easily) and strong network externalities. In the early days of the industry, rms mostly use a combination of two-part prices, where they select between di erent levels of a one time access fee and a periodic subscription fee, Meagher and Teo (005). Gradually, games which allow players to play for free started to emerge, these are know as "free to play" games. One source of revenue for these games are in-game advertising which appear as pop-ups while consumers play the game. In recent years, a new pricing model for "free to play" games has emerged in the form of virtual items. The purchase of virtual items is optional and gamers can play a game without buying anything. Virtual goods are understood to refer to objects such as characters, items, currencies and tokens that exist inside various online games", Lehdonvirta (009). Of the 93 "free to play" MPOGs listed in Wikipedia, 60 involves the sale of virtual items and only 5 used advertising,wikipedia (009) 1. One such notable game is MapleStory, a game by Korean based company exon. exon posted $75 million pro t on $30 million in revenue in 005, this is a large proportion of pro ts when compared to EA games (the world s largest game publisher) who posted $36 million pro t on $.95 billion of revenue in 006. In 008, exon s U.S. revenue more than tripled to $9.3 million from $8.5 million the prior year, Wing eld (008). The "free to play" with virtual items business model is interesting as whether consumers are willing to buy virtual items (instead of just playing for free) is questionable. Another consideration is whether pro ts are high enough to support the pool of non-paying gamers. 1 See Appendix for a full list of "free to play" games.

3 To start o, we need to understand why consumers are willing to pay for virtual items. Lehdonvirta (009) analyzed 14 existing online games by interviewing users and players. Lehdonvirta takes a sociology of consumption perspective and suggests a detailed set of item attributes that drive virtual item purchase decisions. The three main purchase drivers were functional, hedonic and social attributes of the virtual items. Performance is a key attribute under the functional category, items you pay for may be more powerful than those you can obtain for free. One may also buy items which make them more powerful or gain points faster. It was found that powerful items which can be bought with just cash are less welcomed by consumers. Items should help players achieve gameplay goals faster and not just give upgrades without any e ort on the player s part. This preserves the prestige associated with hard to get items. Many items which are highly desired lack performance attributes, consumers point to visually attractiveness as a reason for buying them. Other than pure aesthetic values, these items may also be desired for their social value as they may de ne the player s individuality. Players may purchase items to appear "fashionable", "stylish" or "smart" to other players, this indicates that virtual items have social attributes. Therefore, other than buying a virtual item to make them stronger or more powerful, gamers may also buy items to improve their physical appearance and social standing within the game. The social attribute of virtual items relate to network externalities in economics, a consumer will enjoy the purchase of a virtual item more if there are more people to admire it. Therefore, a virtual item is more valuable if the number of other players is high, we include this attribute in our model in the next section. Economic research in the area has concentrated on analysis of the virtual world and market interactions within those worlds, this line of research is lead by Castronova (001). The paper analyzed a speci c virtual world, orrath, which exists in the game Everquest. Castronova looked at the both microeconomic and macroeconomic factors in orrath s economy. Microeconomic factors include the analysis of trading between players and macroeconomic factors involves trade to the real world. Players may sell items for actual cash, the orrath to U. S. exchange rate is estimated to be around USD Our paper does not look at economic interactions within the game but rather between the rm and consumers. This is di erent from Castronova (001) and other similar papers discussing the virtual economy. Theoretical pricing models of MPOGs are less discussed in economics. One paper which examined the pricing behavior of MPOG rms is Meagher and Teo (005). In Meagher and Teo (005), the rm is given the pricing choice of a one time access fee (A) 3

4 and/or a periodic subscription fee (p), a two-part tari is used. It is assumed that there is a limitation of server capacity and consumer will face negative externalities if congestion occurs. It was found that (given a capacity limit) there exist a multiple equilibria of prices where p is a function of A. This means that rms can choose di erent combinations of p and A to achieve optimal pro ts. This result is consistent with real life situations where rms adopt a two-part tari model. There are rms which choose a large A and charge no periodic fee p, and there are rms with no A but charge p instead. There are also rms charging both types tari s. This model explains the two-part tari scenario but does not explain "free to play" games. In "free to play" games, prices of virtual items are decided and the choice to purchase is left to consumers. In the next section, we attempt to explain the use of virtual items with a economic theory model of heterogeneous consumers and network externalities. The Model In real life, we will observe that the amount of virtual items vary from consumer to consumer, homogeneous consumers would not be appropriate in this case. To model the "free to play" virtual items scenario, we rst require that consumers be heterogenous in their gaming preference. i represents consumer i s preference for playing the game. is assumed to be distributed uniformly between 0 and 1. Thus, the population density is normalized at 1. Consumers are heterogeneous in, this follows from Shapiro (1983) s treatment of consumers who are heterogenous in tastes for quality. Consumers consume either zero or one quantity of the game and/or the virtual item. T represents a consumer s total cost of playing the game, this is assumed to be constant for all consumers. T can also represent opportunity costs, the consumer s next best alternative to playing the game. is the total number of consumers who play the game. Consumers will experience positive network externalities and this increases with, the more players there are, the more enjoyable the game is. This comes from the social interactions within the game which players enjoy. The larger a consumer s game preference,, the more network externalities he will enjoy. Consumer i s utility from playing the game is de ned as: u i = T (1) Although T is assumed to be constant, the heterogenity in translates over to opportunity costs. Consumers with low will be a ected alot by T and consumers with high are less a ected. 4

5 Consumer i will only play the game if T : We assume that each consumer can buy one virtual item. p is the cost of a virtual item. The additional utility derived from buying a virtual item is given as: v i = f() p () f() is a function increasing in ; a consumer will derive higher additional utility from buying a virtual item. The larger his ; the more utility he will derive from buying a virtual item. v i is increasing with, this incorporates the social aspects of buying a virtual item from Lehdonvirta (009). A larger amount of other players to interact with will increase the value of the social attribute enhancing virtual item. Consumer i will buy a virtual item if f 0 ( p ). If we assume a functional form of for f(); this condition becomes p p. To maintain consistency in the setup, we assume that only a consumer who will play the game will buy a virtual item, the follow condition has to hold: Condition 1 r T p or p T Lemma 1 There are three groups of consumers. i) A high preference group with 1 p p ; who will play the game and buy a virtual item. ii) A medium preference group with p p > T ; who will play the game but not buy an item. iii) A low preference group with < T, who will not play the game or buy an item. The division of the population can be depicted in the following diagram: (3) Figure 1: Distribution and division of consumer types Given Condition 1, consumers with the lowest game preference will choose not to play the game. Consumers with intermediate preferences will pay the game but not buy the 5

6 virtual item. Only consumers with the largest preferences will want to play the game and buy the virtual item..1 Equilibrium number of players Following Lemma 1, we can derive the equilibrium number of game players in the market which we can use to calculate the optimum price of a virtual item. Proposition When opportunity costs of playing the game (T ) satis es: a) T > 1 ; no consumers will play the game. 4 b) 0 T 1 = T, the total number of consumers playing the game is given by = 4 1+ p 1 4T. d dt < 0; the number of players decrease with opportunity cost. Proof. is the total number of players. Any consumer with T will play the game. Consumer population is uniformedly distributed and equal to 1. is given by the sum of the high and medium preference group. = 1 T (4) solves to be 1p 1 4T. We assume that d < 0 as increasing opportunity costs should dt decrease the total number of players. The valid root is thus: = 1 + p 1 4T (5) is the equilibrium number of players in the market. For T > 1 4 ; cannot be de ned. Since T cannot be negative, only exist for 0 T 1 4. Thus, there is an upper bound on T, T, where no one plays the game if exceeded. When opportunity costs are higher than the upper bound, T, all consumers prefer not to play the game. Only when opprotunity costs are su cently low, will consumers nd it worthwhile to play the game. When there are no opportunity costs then all consumers will play the game, = 1.. Pro t Maximization A MPOG rm o ering a "free to play" game will have to incur costs for all consumers who play the game regardless of whether they buy the virtual item. Other than being the equilibrium number of players in the market, is also the quantity of per unit costs incurred by the rm. m represents this per unit cost or constant marginal cost. The 6

7 rm s revenue on the other hand is determined only by the number of players who buy p virtual items (1 p ), this comes from Lemma 1. Revenue from this smaller group of consumers need to cover the costs incurred by the larger group for the rm to be pro table. Proposition 3 Given the existence of a group of consumers willing to play the game (0 T T ), the pro t maximizing price is p = (1 + p 1 4T ). dp 9 dt as opportunity costs decrease. Proof. The rm s pro t is given by: < 0, price increase = (1 r p )p m(1 T ) (6) where m is the constant marginal cost per player and xed cost (if any) are normalized to zero. Substituting, we get: = (1 s p + )p m(1 ( 1+p 1 4T ) p 1 4T ) (7) The rm maximize pro ts by choosing p: By equating the rst derivative to zero, we nd the optimal p to be: p = 9 (1 + p 1 4T ) (8) To determine if p is a global maximum, we check the = 3 p q 8 T p 1 4T 1 1 p p 1 4T 1 is negative for all values of 0 T T. p is a global maximum and is positive given that 0 T T holds. p is decreasing in T, as opportunity costs, T; gets larger, the amount that can charged for p is lower. Conversely as T gets lower, p increases. Substituting p into pro ts yield: = ( 4 7m )(1 + p 1 4T ) 54 Pro ts decreases with marginal cost m, there will exist an upper limit on m where pro ts become zero. For pro ts to be positive, we require m < 4 7 = m, where m is the upper 7

8 bound on marginal costs. Where m < m, we nd that pro ts are decreasing with T. Large opportunity costs, T, will impede the rm s ability to pro t from the game...1 Checking validity of results To ensure consistency of results we check that Condition 1 holds. p T, the number of consumers playing the game is larger than or equal to the number of consumers buying virtual items. Substituting p and, we obtain: 9 (1 + p 1 4T ) T =( 1 + p 1 4T ) (10) This inequality is true for 0 T < T = 1 4 : Given that T is lower than T and the pro t maximizing price of a virtual item is charged, the number of buyers of virtual items are lower than the number of game players. There exists game players who do not buy any virtual items. The division of consumers are as described in Figure 1. 3 Discussion This paper examines a heterogeneous consumer model with positive network externalities and the sale of virtual items. The model presented can help to explain how rms using the "free-to-play" model can be pro table through the sale of virtual items. Although simple, the model presents some interesting implications. For a rm to use the "freeto-play" model, it must make sure that consumer s opportunity costs (T ) and marginal costs are kept low. We found that when opportunity costs exceed a threshold level ( T ), no one plays the game even though its "free-to-play". Therefore, if a rm wishes to sell virtual items via the "free-to-play" model, it must ensure that consumers face little opportunity costs. For games which requires players to spend time learning how to use the controls and familiarize themselves with the game (high opportunity costs), the "free-to-play" model may not be feasible. Pro ts are found to be decreasing with T (opportunity costs). To charge higher prices and earn larger pro ts, rms also need to lower consumer s opportunity costs of playing. Ways to reduce opportunity costs includes making the game easily accessible, reducing startup costs (make it easy to learn how to play the game) and increase entertainment value of the game. 8

9 Another condition required for the "free-to-play" model to be pro table is that marginal costs cannot exceed an upper bound, m. In high tech industries like MPOGs, marginal costs such as distribution and production costs will be low, but marginal costs can still be high if much customer service and technical support is o ered. Therefore, "free-to-play" games cannot o er much customer service and technical support (especially to consumers who do not buy any virtual items). This can be evidenced in real life games, most "free to play" games o er minimal customer support. Instead, consumers from their own support base in online discussion forums. The distribution of is assumed to be uniform, this would not be the case in real life. Firms may be able to skew this distribution to the left by creating strong preferences for the game and virtual items. Oh and Ryu (007) suggests some game designs to e ciently accommodate items-based payment models in online games. Some strategies suggested by Oh and Ryu are: 1. Balance between items which can be bought with cash and those that can only be obtained through gameplay. Build synergies between the two.. Items that are bought solely for ornamental purpose should be permanent. 3. Items with functions meant to assist in gameplay should be designed to last for a variety of terms based on the amount paid. 4. Do not disclose actual data of how an item can increase ability, use descriptive text instead. 5. Sell virtual items during speci c events such as Christmas. Further work could extend the model to the game design and marketing stage, where rms can in uence the distribution of by choosing the amount of game development and marketing. Generally, virtual items are designed by artists and designers and the process rarely involves economic analysis. The choice of virtual item attributes should be made strategic, to maximize consumer value and pro ts. The results from our model provide insight to MPOG rms using virtual items sales. Other than a "free-to-play" model with virtual items, one can also consider advertising as a form of revenue. The rm may also choose the more traditional two-part tari model with a one time access fee and/or a periodic subscription fees. Future analysis can attempt to endogenize the choice of pricing model. Also not discussed in this paper is 9

10 the possibility of negative or congestion externalities as described in Meagher and Teo (005), this aspect can also be included in future work. 4 Appendix References Castronova, E., Virtual Worlds: A First-Hand Account of Market and Society on the Cyberian Frontier, CESifo Working paper Series o. 618 December 001, Meagher, K., Teo, E. G. S., 005, Two-part tari s in the online gaming industry: The role of creative destruction and network externalities, Information Economics and Policy 17 (005)

11 Lehdonvirta, V., 009, Virtual item sales as a revenue model: identifying attributes that drive purchase decisions, Electronic Commerce Research 9(1-), Springer, Forthcoming Oh, G., Ryu, T., 007, Game Design on Item-selling Based Payment Korean Online Games, In Proceedings of DiGRA 007 Shapiro, C., 1983, Optimal pricing of Experience Goods, Bell Journal of Economics vol. 14, no., Autumn 1983, pp Wing eld,., 008, Korea s exon Bets on Sales of Virtual Gear for Free Online Games, Wall Street Journal (Eastern edition)., May 3, 008, pg. B.1. Wikepedia, 009, List of free massively multiplayer online games, Available from: < Accessed: 14 April