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78 Seiten, Note: 1,3
2.2 Internet Economy
2.2.1 Online Communities
2.2.2 Network Effects
2.2.3 Critical Mass
2.2.4 Lead User
2.3 Gaming Market
2.3.1 Historical Evolution
2.3.2 Gaming Communities
2.4 Design of an Online Gaming Community
3.1 Operationalization and Measurement Instruments
3.2 Online Survey
3.2.1 Survey Items and Inventory
3.2.2 Conceptual Design of the Online Questionnaire
3.2.3 Technical Implementation
4.1 Online Questionnaire
4.2 Statistical Analysis
4.3 Results of the Lead User Influence
5.1 Scientific Discussion about the Approach
5.2 Empirical Results and Implementation
5.3 Further Scientific Opportunities
6. Conclusion and Future Work
7.1 Abbreviations and Glossary
7.2 Figures and Tables
Figure 1: Critical Mass and its effects on the network economy
Figure 2: Examples for games from the four periods of gaming
Figure 3: Illustration of the underlying database with ASP support
Figure 4: Boxplot: Distribution of players’ age
Figure 5: Distribution of the value favourite game-type
Figure 6: Distribution of the value game-console
Figure 7: Illustration of the interest in game mechanism
Figure 8: Illustration of the free rider problem: interest in add-ons
Figure 9: Illustration of the interest in in-game online communities
Figure 10: Distribution of the lead user score amongs participating users
Figure 11: Out-of-game social contact as a general long-term motivation
Figure 12: Screenshot of the online questionnaire
Figure 13: Distribution of the value gender in the online survey
Figure 14: Distribution of the MOS score for the statement
Figure 15: Distribution of the MOS score for the statement
Figure 16: Number of participants at the online survey
Figure 17: Illustration of the players’ experience with computer games
Figure 18: Illustration of the interest in contact with producers
Figure 19: Illustration of the activity to find other players in-game
Table 1: An overview about the different sources of income for online communities
Table 2: An overview about the different operationalization methods
Table 3: Possible effects of multiple participations by the same user
Table 4: The online questionnaire and its items for demographic values
Table 5: The online questionnaire and its items about lead user determination
Table 6: The online questionnaire and its items for user interaction
Table 7: The online questionnaire and its items for further game related aspects
Table 8: Overview about the participation at the survey
Table 9: Overview about the MOS scores of the lead user related questions
Table 10: Overview: MOS scores of the online community related questions
With the rapid growth of the Internet, a completely new digital environment was created. Hence, old economic rules, price policies and customer interactions are accentuated and replaced by newer versions that include the usage of the information technology. The new “Internet Economy” offers an enourmous amount of perspectives, which penetrate every sector of the economy.
With the fast evolution of the Internet, new aspects like network effects need to be considered, that have an influence on the role of the customer. Generally the amount of available information in the virtual world exceeds the real world information by far; users are forced to limit their perception in order to prevent an information overflow.
One important aspect of the Internet economy is the existance of user communities; virtual places where people with similar interests can discuss a common topic and share experiences. As a motivation from a managerial perspective, these communities can be used to integrate the demogrphic data of each user into the customers database and even aquire potential new customers. Also lead users and their potential ideas for innovations can be gathered from an online community as long as it is managed correctly and offers a high attraction for the specific user group. Especially the role of the lead users for the creation of an online community needs to be evaluated in order to predict future evolution in the gaming market.
This thesis aims to analyse the lead user perspective of an online community at the example of a computer gaming related community. The significant importance of professional players (as idols for other players) and their influence on a potential online community will be empirically evaluated due to a questionnaire and a statistical analysis. Furthermore additional demographic factors (such as age, location, gender, education) as well as game related factors (console type, gaming experience, etc.) will be gathered for further statistical correlation. Afterwards the findings about professional online players and their influence will be evaluated and the results will be used to create guidelines for a successfull creation of a game- orientated online community.
The rest of the thesis structures as follows: Section 2 introduces the necessary background information with regards to important aspects of the new Internet economy (such as online communities, network effects, critical mass and lead users) and the gaming market; Section 3 describes the scientific approach (online survey) in detail; afterwards Section 4 features the analysis and the statistical evaluation of the empirical data; Section 5 includes the discussion of the results as well as critics about the approach; Section 6 gives a short overview about the further implications of this thesis and Section 7 concludes the main findings and offers an overview about futorious work.
This section gives an overview about the high relevance of the Internet economy; especially the motivation to analyse the current Internet situation and use the findings in order to create a successful solution for an online gaming community. Furthermore the two central aspects of the thesis are explained in depth: first the Internet economy and its effects (such as network effects, lead user influence or critical mass) and second the computer gaming market. Since the thesis covers a large field of different scientific approaches, it is important to focus on the most relevant information.
Due to the rapid growth of the Internet and its influence on nearly every human activity, one can not deny that successful business solutions must take the opportunities of the virtual world into account in order to be successful. By not using the new opportunities one will receive comparative disadvantages amongst potential competitors. Not only the communication has become faster (due to the high communication speed within the virtual world), also the general usage of the Internet has completely changed.
It is necessary to analyse the effects of the Internet economy for every individual business scenario, in order to react most efficient. In the case of the computer gaming industry, the fastest growing entertainment market, one can clearly see that the usage of the virtual environment for advertising or product placements has already become the standard. However, different factors must be considered like the enormous fixed costs for software evolution and the comparably low costs for reproduction lead to special market conditions.
Since the current market behavior of successful game publishers in the computer gaming industry is changing rapidly (just like the needs and expectations of their customers), one can use the insights of the Internet economy in order to create new ways of approaching the customers. Thus this thesis focuses on the importance of user communities (one possible way to use the opportunities Internet economy) and analysis their influence in the computer game market.
In order to understand the underlying background information it is necessary to clearly define the important phrases. Since the Internet economy is difficult to define precisely, one must look at several definitions to understand the relevance of this term:
“In today's Internet economy, knowledge, information and time form the basis for competitive success; markets have evolved into broad, highly inclusive environments driven by common technology standards and low competitive barriers.”, (Hartman et al., 2000, p. 25).
“The Internet economy refers to conducting business through markets whose infrastructure is based on the Internet and World Wide Web. An Internet economy differs from a traditional economy in a number of ways, including: communication, market segmentation, distribution costs, and price”, (Encyclopaedia Britannica, 2007).
Both definitions share a common aspect; they define the Internet economy through different economic principles, goods and services that are related to the Internet. Since the influence of Internet for the economy is already significant and still growing, it is fundamental to understand the consequences of the technical evolution.
A brief overview about the most important consequences of the Internet economy is to be found in (Zerdick et al., 2001, pp. 16-20), where ten thesis about the Internet economy are explained:
- 1) The digitalization of the added value reaches all scopes of the economy
- 2) Critical Mass is going to be the key factor for the network economy
- 3) Traditional added value is going to erode
- 4) The battle for attention is going to be the central aspect of competition
- 5) The new complex added value requires competition and cooperation
- 6) Mass markets will be individualized through cost reduction and differentiation-strategies
- 7) Electronic commerce is going to be normal
- 8) Digitalization simplifies the product and price differentiation
- 9) Current administration models are going to be obsolete
- 10) Normalization at the listing on the stock exchange will lead to a natural selection of the Internet companies
With regard to the topic of this diploma thesis rule number 2, 4 and 6 are interesting in particular. The rule of the critical mass will be explained in depth in Section 2.2.3, meanwhile the battle of attention and the higher individualization need to be explained in depth.
The cost trend in the Internet economy might be one of the most important aspects, as Stelzer (2006) notes, the development costs have increased, meanwhile the production and distribution costs are only marginal. This cost distribution indicates that the Internet economy can be seen as an accentuation rather than a complete revolution, because a similar distribution of costs can be observed in other areas like media or research and development much earlier. The major difference in between these examples is that the Internet has a much higher influence on all other markets.
A typical example is the creation process of software; while the development can take up to millions of dollars, the distribution (sometimes available through direct downloads) has nearly zero costs. This leads to various problems, such as free-riding (copying the software without permission) or in-transparent pricing policies. Especially online services are often expected to be free of any charge, which leads to the question why companies should be motivated to offer free services.
The reason for the strong change in expectations is that the resources have drastically changed. One of the first approaches towards the Internet economy was the definition of the scarce resource, which initially should be information. It turned out that the amount of information considerable increased with the Internet. In fact, the extremely low entry barriers of the virtual world have lead to a large amount of different companies that all offer their services.
Therefore the user needs to select the most appropriate offer, although the available time and attention is not unlimited. As Lanham (2007) already argued:
“Must it not be human attention, the n that converts raw data into something humans can use?”, (Lanham, 2007, p.35).
The underlying argumentation assumes that if the economy is the allocation of scare resources and if it is true that we are moving away from a goods economy towards an information economy then human attention must be the scarce resource.
This is relevant to keep in mind, since on rapid growing markets (like the computer game industry) it is vital to receive a minimum market share in order to cover the development costs. Attention is the required resource for the market share, which leads to the fact that one should look for efficient ways of maintaining customers’ attention. A good example of the computer gaming industry can be found in Burgelman et al. (2003), where the competition of Nintendo and Sega is described in depth.
In order to understand the influence of online communities, one must comprehend in which way they evolve and what they can offer in an economy with only one scarce resource: which is attention.
First of all it is necessary to define the term online community: “An online community is a group of people that primarily interact via some form of mechanism such as letters, telephone, email or Usenet rather than face to face. If the mechanism is a computer network, it is called an online community.”, (Encyclopaedia Britannica, 2007).
As Hagel (2006) explains, the user groups initially have no commercial background, they evolve from news groups. Since most of the companies use the Internet as an opportunity to present their services on their own web pages and through banners, their strategy is based on the expectation that the customer stays long enough to gather the required information. Because of low involvement and the significant general information overflow in the Internet, such a behavior is very rare.
Furthermore Hagel (2006) explains that user communities are described through five significant attributes:
- 1) A specific central point of interest (that defines the common focus)
- 2) The opportunity to integrate content and communication
- 3) The usage of information that are contributed by the users themselves
- 4) The access to different competing producers
- 5) A commercial orientation
In particular the commercial orientation needs some more clarification, because not every online community has a direct commercial background. However since the “producer” of the online community needs to cover expenses, some kind of financial compensation needs to be achieved.
The most common sources of income are explained in detail in Hagel (2006, pp. 60- 65). Generally the sources of income can be classified as direct and indirect sources. Table 1 features an overview about the different sources of income.
illustration not visible in this excerpt
Table 1: An overview about the different sources of income for online communities (cp. Hagel 2006, pp. 61-65)
Direct rates from members are rather exceptional, because of the significant amount of different user communities and the value of participating members at each community, the owner of the community aims to increase the user numbers as fast as possible. Advertisement has become one of the most important sources of income, since users accept a certain amount of advertisement if the service of the community is free of charge otherwise.
In order to be more efficient in placing advertisements on the Internet one has to observe the behavior of the users to analyse how their attention is spend. Most of the users have at least one particular field of interest (like golf, computer games, cars, etc.); these interests can be specialized, so users tend to share their experience with others as long as they share a common interest.
Knowing the customers desires gives the producer the opportunity to satisfy the individual needs, therefore building a closer relationship and create a higher loyalty. From the producers point of view a user community offers different advantages.
First of all if the interest of the community correlates with the available services of the cooperation, the users will pay more attention for the advertisement through the higher general involvement. In the case of this thesis, possible ways for the gaming industry should be evaluated. The members of an online gaming community will share a common interest in either a particular type of game or computer games in general. Therefore the better the advertisement matches the general interest, the more likely the members will follow the advertisement in order to receive more information.
Another important aspect is the usage of underlying customer data. The user discussion about products (such as games) can lead to valuable insights about problems of the end-users and therefore offers opportunities to further improve existing products and services. In an online community the users will discuss their needs and experiences with other users, which offer a great opportunity to gather this valuable information.
One of the most significant influence factors for the Internet economy is the aspect of network effects. In order to understand their influence on the customer (especially with regard to the computer gaming industry) one must closely define the term first of all:
“Von Netzeffekten spricht man, wenn der Nutzen für einen Konsumenten von der Anzahl der anderen Konsumenten abhängt, die das gleiche oder ein kompatibles Gut erwerben“, (Morasch, 1998, p. 1). Translated into English, this definition means that network effects occur if the individual gain for a customer depends on the number of other customers that buy the same or a compatible good.
Another definition highlights the potential value more: “A network effect is a characteristic that causes a good or service to have a value to a potential customer which depends on the number of other customers who own the good or are users of the service”, (Encyclopaedia Britannica, 2007).
Both definitions however share a common aspect; a user receives a higher benefit from a good as soon as more other users are utilizing it as well. The most common example for network effects is the telephone, as long as only one user would own a telephone, it would be completely useless. With a growing number of potential people to call, the gain from having a telephone significantly increases.
A more detailed differentiation of network effects can be found in Katz and Shapiro (1985), where they introduce the terms direct and indirect network effects. The direct network effects arise straight from the diffusion of the good (like the users’ gain of having the opportunity to call all friends through the telephone). The exact opposite are the indirect network effects, these describe alternating dependencies between the consumers, without having a direct connection to each other (like spill over effects or economies of scale).
The most important results of the scientific evaluation of network effects are concluded in König and Weitzel (2003), where two main statements are given:
- 1) Network effects imply multiple equilibriums; however a lock-in situation of
the market with a single monopoly technology is expected.
This finding describes that the direct network effects (personal gain of having as many other users with compatible technology as possible) often lead to the situation, where one of the competing technologies will reach a critical mass of users. Once this number is reached, as a consequence the direct network effects will motivate user from competing technologies to change (a common example is the battle between video formats of VHS and BETA). The so called lock-in situation promotes the single technology and because of the sunk costs (investments into the technology, like a video-recorder with a specific format), users are unlikely to change to another comparable technology. This coherence leads to the following conclusion:
- 2) Network markets (especially software markets) are typically instable, which
means that competing technologies seldom coexist over a longer period of time. The decision for one of the two technologies can be rapid.
With regard to the computer gaming market, one must keep in mind that the described network effects strongly influence the production of computer games. Nowadays the production cost of a top computer game can easily exceed 50 billion dollars (like Everquest 2 or Quake 4) during their development, the publishing and distribution costs on the other hand are nearly zero.
New concepts and ideas are implemented rapidly and innovations are only short living, as soon as a gaming concept proves to be helpful for the user, it will generally be copied by every competing game. The conditions on the computer gaming market therefore strictly promote to build a large customer base, in order to finance the initial fixed development costs.
The term critical mass has a close relation to the network effects. A good explanation of this aspect can be found in Kerbel (2004), who introduces the critical effects:
“(…) consumers will abstain from purchasing such a good unless they believe that a sufficient quantity of that good will be sold to justify paying the market price. This requirement to attain a certain minimal market size has been termed the “critical mass” problem (…)”, (Etzioy, 2002, p. 2).
This statement indicates that the high amount of fixed costs, which are generated for both the producer and the customer, can only be offset by reaching a certain number of participants (the critical mass). This research aspect is mainly based on Oren (1981).
From a consumer’s perspective, the fixed costs will be offset due to the higher direct and indirect network effects. At the example of the telephone technology, a user would be compensated for the initial costs of buying a telephone, by having the opportunity to call a certain number of other people. If this number is high enough the personal gain compensates the expenditures.
From a producer’s point of view, the fixed costs for developing the technology must be offset by paying customers. The critical mass describes the break even point, from which the producer has successfully obtained all initial investments and each additional customer will generate profits.
Especially with regard to the usability of a certain technology, the critical mass plays an important role. Because of the instability of the network markets and the seldom coexistence of competing technologies over a longer period, each of the competitors will try to reach the critical mass as soon as possible. A common follow-up reaction after the critical mass is reached can be observed in various network situations: usually new users are highly attracted, because their individual gain (which is generated through the network effects) is comparably much higher than in other networks. Therefore it is common that as soon as the critical mass has been reached, one technology will dominate the whole market. One common example of the past is the design of Internet browsers, where Netscape and Microsoft both aimed to build the standard; in the end Microsoft succeeded and dominated the market.
illustration not visible in this excerpt
Figure 1: Critical Mass and its effects on the network economy (Compare to Kerbel, 2004, p. 9)
Figure 1 illustrates the effect of a critical mass: during phase 1 the early adapters will buy the technology, the network itself is not big enough to satisfy the common customer due to high network effects. At point A the critical mass is reached (one should be aware that this does not necessarily need to be at 20% of the market share).
Once the number of subscribers exceed the critical mass, phase 2 will begin. During this period a rapid growth can be observed, a lot of customers will buy the technology and the network will rise.
Two further aspects can be observed as well: first of all, if the critical mass is not reached in time or if a competing technology reaches a critical mass, then the customers will turn away from the less popular technology and favour the new common standard. Therefore it is necessary to reach phase 2 as soon as possible, to realize the enormous growth.
The other important aspect is the existence of a second critical mass, due to the increasing size of the network and its complexity, higher costs will occur for the single participant, which means that every additional participant will produce negative network effects. A common example would be an online chat room, where a certain number of users are required to keep a conversation going, meanwhile too many users would produce a spam, which constantly decreases the utility for all participants. This effect is illustrated through point B, hence in phase 3 the growth will be either not existing or significantly decreasing (compared to phase 2).
One of the most important aspects in the network economy is the existence of lead users; the widely accepted definition of this term is introduced in Hippel (1986):
“1) Lead users face needs that will be general in a marketplace - but face them months or years before the bulk of that marketplace encounters them, and
2) Lead users are positioned to benefit significantly by obtaining a solution to those needs”, (Hippel, 1988, pp. 792-793)
The existence of these users fundamentally change the perception of innovations, even a completely new method (lead user integration) is introduced. The idea is to integrate motivated lead users into the development in order to use their individual needs to produce a solution for upcoming problems. Examples can be especially found in the sports section, since the professional athletes often have needs that the next generation of hobby athletes will also aim to have.
The integration of lead users does not always only have positive aspects, since it is very difficult to determine whether a person is really a lead user or just an expert in his/her field. This aspect will be fundamental for the computer gaming market. Furthermore even after determining enough lead users, it is still necessary to bring them together in a productive environment in order to create solutions for their needs. Sometimes, even with the correct number of lead users, their problems can not be solved due to technical issues or financial problems (for example technical limitations of computing power or physical limitations of sport gear).
Before one can concentrate on the example of the computer gaming market, it is necessary to ensure that the lead user concept can be assigned for consume goods (like video games). As Springer et al. (2004) and Hippel (1988) argues, the lead-user concept can be assigned at consume goods; common examples like the development of sport gear and outdoor equipment further underline this thesis.
The computer gaming market and its users can be compared to athletes in some perspectives. As Fritsch (2006) shows, the average gaming time of players is about 30 hours a week, meanwhile in extreme cases it can reach up to 90 hours. This intense computer interaction leads to a dedication and a deeper insight of game mechanism. Since the computer gaming scene has its own terms, it is vital to differentiate them.
Several games are approached in a professional way; the most common example for this is Starcraft, which is currently the national sport in South Korea. The heavy users participate in world championships and even a professional league exists. An noticeable term in this context is the “pro-gamer”, which describes a user who is professionally playing computer games as an electronic sport.
Not only their understanding of the underlying game mechanisms is significantly higher compared to a casual player; they also greatly influence other users. First of all, the professional users often have a direct contact to the game developers. They are invited to pre-test upcoming software and their feedback can influence how the game evolves. Therefore they already help to conceptually design the game-world and develop a growing influence on the game rules in the virtual environment. On par with that, they are often guides for a lot of other players, who imitate their tactics and adopt their style to play.
Combining both effects, they further increase the importance of lead users (progamers) in the computer gaming market. They do not only face needs before the casual user does, sometimes they also actively help to design updates for the current games and they also act as a guide for others.
In order to receive a critical mass or benefit from network effects in the computer gaming market, it is necessary to find a way to first of all identify the lead users and then satisfy their needs, since they have a high influence on the rest of the casual players. It is important to point of that this influence is one of the major factors to reach the critical mass for a computer gaming online community for two main reasons. First of all their behavior is adopted by other players, because they act as guides. Second, they are opinion leaders in the game scenes, which reflect their social contact to many other players. If the features of an online community are adopted by them, then their social environment will receive a positive feedback and will be motivated to participate as well.
The growth of the gaming market in the last five to ten years reflects the acceptance and importance of multimedia entertainment. As a part of it: the total revenue of the gaming industry already exceeds the film industry by far (box sales); and it is still growing. Within this evolution one can observe that especially interactive multiplayer and mobile applications are growing rapidly.
Without a doubt this evolution also significantly increases the number of related research approaches and hence their scientific importance. Nevertheless the research field of gaming contains a wide variety of problem fields, ranging from graphical performance and efficient network structure design up to social influence factors like player behavior.
Generally the majority of computer games are played on either a personal computer (PC), a console (Play station, X-Box, Wii, Game Cube, etc.) or a portable device (Sony PSP, Nintendo DS, and Game-boy). The current gaming multiplayer scene is made up of four main game types: FPS (first person shooter), RTS (real time strategy), RPG (role playing game) and SG (sport games). Each of them covers its own set of problems and its own set of players.
Together with the increasing social acceptance of mobile games, one can clearly observe the rapid changes in technical equipment of the devices. For instance current mobile phones feature colour displays, RAM and hard disks in order to allow them to run mobile computer games. As a result of the technological change the gaming industry will further orientate itself towards the next generation of gaming, which is mobile. As an example: the overall revenue of mobile phone games in Europe increased from 0.3 billion dollars in the year 2000 to an estimated 6.17 billion dollars in the year 2006 (which is nearly 21 times as much).
The computer gaming market currently shows two dominant trends. First of all, the number of simultaneously playing users increases. The aspect of multiplayer modes has become a common feature. The other remarkable aspect is the mobile integration. Due to the increasing technological opportunities mobile gamingapplications are rapidly increasing. It is important to keep both aspects in mind, because they reflect current interests of the computer gaming community.
The historical evolution of computer games can be divided into four main periods. An overview about the details of this classification is given by Stahl (2007).
1) The early years (1952 – 1970): During this period the first computer games are developed, mainly due to the limited hardware power and the very limited displays these games clone simple real life games, such as tic tac toe or ping pong.
2) The golden age (1971 – 1983): With the development of personal computers and consoles for the home market, the gaming development drastically changed. The computer games feature a much wider set of opportunities, as well as new game modes (such as multiplayer).
3) The modern age (1984 – 1994): A further significant change in computer games started with the availability of networks (such as local networks or the Internet). Accordingly, the development of consoles and 8-bit as well as 16- bit systems further increased the game opportunities. Multiplayer modes became more common and colour games were defined as the standard.
4) The “Next” Generation (1995 – 2007): With the rapid growth of the Internet, a multiplayer opportunity in virtually, every computer game has drastically changed their play-style. The high demand for better graphical animation also significantly increases the development of new graphic adapters, video cards and computing methods. Therefore computer games are one of the main reasons for the rapid development of new network and video solutions.
Beside the mentioned development of personal computers, also the market for consoles is significantly growing as well. Since some computer games require technical knowledge, the consoles offer an alternative method of approaching video games with a simple “click and play” strategy.
The current evolution has not come to an end yet. Due to the high demand for multiplayer games and the opportunity to create mobile devices, the computer gaming market will grow even further. Therefore it is vital to understand the upcoming needs in order to create successful application for the next generation of games.
illustration not visible in this excerpt
Figure 2: Examples for games from the four periods of gaming (Compare to Stahl, 2007)
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