The influence of customer’s perceived uncertainty on buying behavior in the video game industry

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The influence of customer’s perceived uncertainty on buying behavior in the

video game industry

Student Nora van Bracht

Student number 10401121

Date January 26, 2017

Thesis supervisor Mr. F.B.I. Situmeang

Study Master Business Administration – Marketing Faculty FEB (Faculteit Economie en Bedrijfskunde) University University of Amsterdam

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Statement of originality

This document is written by Student Nora Karin Margriet van Bracht who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Abstract

Game companies are performing in a dynamic, competitive industry. This brings a lot of uncertainty. One of the reasons is that the creative industries are one of experiential goods instead of utilitarian goods. This means that customer’s do not necessarily need the products in everyday life and

consumer’s do not know on beforehand if they like a game or not. This makes it hard for a game firm to know if a certain game will sell well. The stakes are even higher because the development and introduction of a game is a very costly and time intensive process. If a game does not sell well, it can have disastrous consequences for the game company. One way of decreasing the risks for game firms is by introducing sequels. These are continuations of earlier published games. There has been extensive research on sequels, but especially in the film industry (Mezias & Mezias, 2000; Sood & Dreze, 2006) . Besides that, the buying behavior of consumers with regard to sequels is still underexposed.

There has been quite some research on the buying behavior of consumers. There has been detected, by numerous studies (Homburg, Koschate & Hoyer, 2005;Wertenbroch & Skiera, 2002; Voelckner, 2006), that several factors are of influence on the consumer’s buying behavior. Examples are the perceived quality and the perceived value. One of the less researched factors of buying behavior is the perceived uncertainty of the consumer. Consumers have, according to the prospect theory (Kahneman and Tversky, 1979), a tendency to see a purchase in gains and losses. Spending money, for example, is a loss, but also the time a consumer is using to find the right product is seen as a loss. Gains can be that you like the product. People have the propensity to weigh the losses heavier than the gains. When consumers is not sure if they like a product, which is the case with video games, they face a lot of uncertainty and are likely to not buy the video game.

There are ways to decrease the uncertainty for the consumers in the game industry, such as reading expert and consumer reviews (Situmeang et al., 2016). Other manners are the use of games from the same brand (brand awareness) such as Nintendo, to lower the uncertainty. One important way in the game industry to classify games is the use of genres. Genre is an important indicator for consumers what to expect from a game. Video games of certain genres share the same

characteristics, such as rules, visuals, and storytelling. These characteristics form the basis for the consumer’s expectations, which is different for each genre (Hsu, 2006). A genre can thus be seen as a risk reducer for consumers in the game industry.

Sequels are even an extremer way to decrease the risk when buying a game. Since a sequel is based on a previous games, consumers better know what to expect. Also game companies like to publish sequels, because the sales figures of the previous game can be used as an indicator of the sales

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4 figures of the sequel and a sequel is cheaper to produce and release. Intellectual Property can be reused and in a sequel, often the same characters, storyline or gameplay are involved.

So, for the game companies as well for the game consumers, games in known genres and sequels are popular. The games are familiar, but have also a few new elements to make sure there is enough difference. This is an example of incremental innovation or exploitative behavior (March, 1991; Tschang (2007). Extensive research (Raisch & Birkenshaw, 2008; Levinthal & March, 1993). has been done about whether an organization should pursue exploitative behavior, explorative behavior or both (ambidextrous). Consensus is that companies should perform incremental innovation to keep the companies viable on the short term, but that are also new innovations and developments necessary to gain competitive advantage. So in the game industry, the introduction of totally new games are also of importance. Since genre and sequels are often linked to the same group of consumers, entering a new genre or with a totally new game in a new genre is entering a new market segment, which is an explorative innovation.

Two ways to measure buying behavior is Purchase Intention and the Willingness To Pay. Purchase intention is a way to find out is a consumers is willing to buy the product at all. Willingness To Pay measures the amount of money a customer is willing to remunerate for a certain product or service. The research question of this research was what the influence of a customer’s individual perception to uncertainty was on the willingness to pay and purchase intention on sequels, games in new genres or totally new games in the game industry. The empirical findings of this study gives answer to this question and have implication that might be interesting for further research or to game companies with regard to strategy choices in game developing.

This study contains a questionnaire about 9 different games, which were divided in 3 different categories: sequels, games in a new genre and a totally different game. Information about the game was provided by an image of the game (including the logo of the publisher), information about the game, information about the publisher and a clear title. Questions were asked about the individual’s gaming behavior, perceived uncertainty, and their opinion about the game. Questions were if the respondents knew what to expect of the game, what the quality was, if they had the intention to buy the game and what price they would pay for the game.

On the basis of the results of this study, it is not possible to say that the customer’s individual perception to uncertainty is of influence on the buying behavior of games. However, when buying a sequel, the consumers knows more (than a game in a new genre and a totally new game) what to

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5 expect from a game. And when a consumers knows more about a game, they have higher intentions to buy the game. With these results we can partially answer the research question.

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1. Introduction

Purchase Intention and Willingness To Pay

Purchase intention and willingness to pay are one of the most researched topics in the marketing literature. After all, the intended results of all marketing efforts are that consumers are willing to pay (more) or purchase more for/of certain products and services.

Willingness to pay (WTP) is the actual amount of money a consumer is willing to spend on a specific product or service (Cameron and James 1987; Krishna 1991). Purchase intent is a measure if the customer has the actual aim of buying the product. It is the plan to purchase a product or service in the future.

Since there already has been quite some research on these topics (Homburg, Koschate & Hoyer, 2005;Wertenbroch & Skiera, 2002; Voelckner, 2006), several factors that influence willingness to pay and purchase intentions have been detected. One of these factors, for example, is the perceived quality, which is defined as the consumer’s judgement about the product’s or service’s overall excellence and superiority (Zeithalm, 1987). On the contrary of objective quality, where there is an emphasis on the objective aspect or feature of a product or service (Rowley 1998), perceived quality is a kind of attitude. Perceived quality is related to product satisfaction, which occurs when the expectations of a product performance or service performance are met of even exceeded. Another factor which can explain the Willingness To Pay is the perceived value. Perceived value has been studied a lot in different settings (Woodruff et al., 1993; Slater and Narver, 2000; Zeithalm et al., 1996) and presents a trade-off between the benefits and losses a customer perceives when buying a supplier’s product or service. Snoj et al. (2004) has distilled from all the different definitions of perceived value some common factors (p. 158):

-value for a consumer is related to his expertise or knowledge, of buying and using of a product; -value for a consumer is related to the perception of a consumer and cannot be objectively defined by an organization;

-the customer perceived value is a multidimensional concept; and

- it presents a trade-off between benefits and sacrifices perceived by customers in a supplier’s offering.

The above mentioned factors have one important attribute in common: they both stress on the importance of perceived experience of the customer. Even though the quality of a product can be objectively high, the customer can perceive that quality as low and this has influence on his/her buying behavior.

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8 Perceived Uncertainty and risk

Another, yet much less researched factor that is of influence on willingness to pay and purchase intent is the perceived uncertainty and/or the perceived risk. But first, what is the difference between the two concepts? Even though perceived uncertainty and perceived risk are often used interchangeably, there is difference between the two concepts. When someone experiences a feeling of uncertainty, the possible outcomes are unknown. With perceived risks, the consequences are known, the person only does not known which of the possible outcomes it will be (Knight, 1948). For this thesis, the outcomes for consumers are clear: they can like the video game or not. But the reason why they do or don’t like the game is not known and this makes the situation therefore uncertain. Since both concepts are applicable to the situation, they are used interchangeably in this thesis, as is also done by invariably marketers before. Knight (1948, as mentioned in Mitchell (1999; 166) even claims that “known probabilities are extremely rarein purchase behavior, and that even when they are available, the consumer is unlikely to think in terms of them”.

It is hard for a consumer to predict on beforehand if they like a game or not, as games are experience based products. This means that the quality of a game is based on a subjective

experience, which makes it very hard for a consumer to assess on beforehand if they like a game or not. Since games are quite expensive, game consumers like to decrease the chance of buying something they don’t like. This can be done in different ways, such as reading consumer reviews (Zhu, 2009) and expert reviews (Reinstein & Snyder 2005), but also by picking something that is slightly familiar, such as a game in the same genre or a game from the same developer (Milewicz & Herbig, 1994). Others like to go for something ‘totally different’.

The amount of risk a customer perceived influences the willingness to pay and purchase intent. If a customer is uncertain if he will like a product, the willingness to pay a high amount of money is probably lower than when they know on beforehand if they will like the product.

Game Industry

Why is the game industry such a good setting to do this research? In this thesis, I will study the influence of uncertainty avoidance of consumers on the willingness to pay and purchase intentions for console games. The game industry is a perfect setting for this research for 3 reasons.

First, the game industry is a relatively new (and therefore not much researched) field and is nowadays a flourishing industry. According to market reports about the game industry games are “rapidly becoming the world’s favorite pastime” and “game companies are becoming global

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9 entertainment companies” 1_{; the growth of the game industry is unstoppable.}

The game industry is a relatively new and very dynamic industry. Different games for different sort of devices are published every day. Over a 25-year period, the industry has grown between 9% and 15% annually (Zackariasson and Wilson, 2010). Nowadays, there are not only game home consoles, such as the Microsoft’s Xbox One (introduced in 2014) and Sony’s Playstation 4 (introduced in 2013), various firms have also released handheld game consoles, such as the New Nintendo 3DS

(introduced in 2014). Games are increasingly popular on smartphones, tablets and smartwatches. Thanks to the upswing of the broadband internet, it is much easier to diffuse games digitally. Due to the introduction of Apple’s iPhone in 2007, another game genre came up: games as an app. And as a result of the increase of development applications, such as Twine and GameMaker, people don’t even need to know how to code in order to make games.

Figure 1: Global unit sales of current generation video game consoles from 2008 to 2016 (in million units). 2

Even though the game console industry is a profitable industry, figure 1 shows that the sales of video game are under pressure. The game industry is a profitable industry, which means more and more firms will enter the market. The emergence of online hand held games as a serious substitute of console games can be a possible explanation for the reduction of sales.

Jansen, Van Den Bosch & Volberda (2006) state that dynamic environments are characterized by “changes in technologies, variations in customer preferences, and fluctuations in product demand or supply of materials”(p. 8-9). Dynamic environments make current product and services rapidly obsolete, which makes it essential to develop new ones (Jansen et al. 2005a). Jansen et al. (2006)

1_{Newzoo Global Games Market Report 2017 Light, retrieved from}_{http://resources.newzoo.com}_. 2_{https://www.statista.com/statistics/276768/global-unit-sales-of-video-game-consoles/}

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10 underline the importance of introducing new innovations that depart from the already existing products, services and market in order to conquer the threat of obsolescence. Those kind of

innovations are called in the marketing literature ‘explorative innovations’(March 1991).Exploration can lead to successful innovations, but it’s also a very risky decision, since the development of new technologies or marketing decisions for which returns are uncertain, unclear and might happen in a distant future (Danneels, 2002).

Explorative behavior in the game industry does not necessarily mean that companies have to come up with world changing innovations, such as the Wii (Subramanian et al., 2011; Verganti, 2009). Competition does not only take place in the area of technology, but also on non-technological factors, such as storytelling, graphics and visuals (Koster, 2010). In exploring new market segments in the video game industry, video game developers usually do this by exploring new market genres. This because specific groups of consumers form certain customer segments and they tend to buy games in particular genres (Greenberg, Sherry, Lachlan, Lucas, and Holmstrom, 2010). So if you expand to a new genre, you do explorative behavior, because you’ll serve a new customer segment. Uncertainty in Game industry

Not only consumers experience uncertainty when buying a video game, there is uncertainty on the firm-side in the game industry. Entertainment products and services such as films and games are, according to Tschang (2009, 990) infamous for having (1) a hits-oriented nature. This means that only an small part of the games are responsible for the largest part of the total revenue. (2) A short product life cycle in the market. This means that even though, the product can be watched/played for years, the product is sold and used for a short amount of time (Epstein 2005, Hirsch 2000) (3) troubles in predicting product acceptance (DeVany 2004). In this thesis, this factor will be further explored.

All these factors tend to reinforce the conservative nature of new product decisions, fostering incremental innovations (where incremental innovations typically involve minor changes to the products’ component). So, firms in the game industry have already the tendency to reduce risk by fostering incremental innovations (Tschang, 2007).

Another effect of a maturing and more mainstream industry is that the competition is increasing. Publishers release titles that are attractive to every niche and every taste. While at one hand the game industries is growing vividly, many game companies have difficulties to survive in this competitive environment. Video games are driven and are dependent of technological

improvements, and costs for those improvements are increasing. As a result, commercial failures are disastrous for most game companies and make them rethink their strategies. One way for game

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11 producers to decrease the risk is introducing game sequels. While companies are attracted to incremental innovations, innovations are vital for survival. Therefore, for a firm’s viability, it is important to pursue as well as incremental innovations, such as a sequels, as completely new games. Sequels, New genres and new games

One emergent trend in the video game industry is the popularity of sequels or games based on licenses (franchises). Since games are very costly to develop and the chance of failure is significant, publishers are less willing to take risks. Knowing that a certain film, comic book or a previous game was successful, gives an indication of the sales of the new game. Publishers can simply look at previous sales charts. Consequences are that there is a lack of innovation in the new games, which is also called incremental innovation. For game producers it is extremely important to sell these kind of games in order to stay viable in such a dynamic and competitive market.

Another way for firms to decrease the risk, but at the same time be innovative, is publishing games in a different genre. In this way, the same knowledge and licenses are being used for different games, but at the same time provides a kind of ‘newness’ the consumer graves for. However, there is still a bigger chance that the consumer might not like the new protagonists or other parts of the game.

The option with the most risk for a game publisher is to release a totally new game in a new genre. This involves a very high degree of risk, but is also necessary once in a while. Innovation means after all progress (Matusik & Hill, 1998; Abebe & Angriawan, 2013). Since the game industry is such a dynamic and competitive industry, Au and Meguc (2005) claim that companies should engage in explorative, risk-taking behavior to break out of the promotion wars. Zahra (1993, p. 324) states: “When rivalry is fierce, companies must innovate in both products and processes, explore new markets, find novel ways to compete, and examine how they will differentiate themselves from competitors. Genres are therefore a necessity to keep the company going.

So competition in the game industry is driven by innovation and technological inventions. But at the same time, consumers do want some familiarity when playing a game. These 2 opposing pressures makes it hard for game companies to innovate. Studios have to compromise between truly creative and listening to the wishes of publishers and consumers. According to Tschang (2007) it is a matter of balancing between this pressures. On one hand, developers are adjusting to exploitation

pressures (i.e. production issues like efficiency). On the other hand, it is expected that games have at least some creativity. This means that there has to a certain degree of innovation, which often happens incrementally. Radical inventions are more rare, but are necessary to keep the game

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12 industry moving and are for a company a potential source of competitive advantage (Such as the Wii).

Incremental games are often successful, because they are not simply replicas of already existing games, but they still contain something new, while at the same time the consumer’s need for familiarity is maintained. A successful game contains the most valued part of the genre (or in the case of sequels, of the previous game) and adds something new.

Research Question

With the above mentioned arguments, it seems logical that console game producers are eager to decrease the risk. At the same time, to keep their companies viable, they also need to release new games. But do the consumers like it? On one hand, consumers do like a certain degree of familiarity in their products. On the other hand, a purchase of a game is seen as a financial “loss” and

consumers want worth for their money and experience something new. Given the literature above, I have come to the following research question:

What is the influence of a customer’s individual perception to uncertainty on the willingness to pay and purchase intention on sequels, games in new genres or totally new games in the game industry? Based on this research question, the following sub-questions were posed:

What is the influence of a customer’s individual perception to uncertainty on the willingness to pay and purchase intentions on video game sequels?

What is the influence of a customer’s individual perception to uncertainty on the willingness to pay and purchase intentions on games in new genres?

What is the influence of a customer’s individual perception to uncertainty on the willingness to pay and purchase intentions on totally new games?

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13 Research Gap

The creative industries have proven its increasing political and economic value during the last decades. Compared to other industries, the creative industries are characterized by innovation, but also by uncertainty. These characteristics demand tailor fit research.

Firms in the creative industry may need to emphasize on different manners of exploration compared to firms in other industries due to its dynamic and challenging nature. There has not been research on uncertainty avoidance in the customer’s buying behavior in the game industry. Also Nakata & Sivakumar (1996) underline the importance on research on Uncertainty Avoidance and forms of innovations: “Although uncertainty avoidance’s tie to new product development has not been explored, the literature suggests that the relationship may be understood in terms of two

dimensions of uncertainty avoidance – planning and risk aversion”. It is hard to assess the quality of a game and the assessment can differ between customers. Therefore, it is hard to plan and it increases the risk in producing a video game.

Since the game industry is a relative new industry, not much research has been conducted. Most research about sequels and genres are found in the film industry (e.g. Mezias & Mezias, 2000; Sood & Dreze, 2006). Since films and games are both experiential goods, there are similarities between these 2 industries, such as the use of genres and sequels and the storytelling plays an important role. One might say that studies on the movies industry can easily be copied to the game industry, but the opposite is true. There are two main differences. First, watching a movie is a passive activity, while playing a game is interactive. Therefore, the experience of watching a game is rather different than the experience of watching a movie. Second, other movie factors, such as the use of “actors” and “star power” and film ratings are not transferrable to the game industry.

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14 Structure

In chapter 2, an explanation is given of the main subjects of this thesis. Concepts such as Willingness To Pay, Purchase Intent, Perceived Risk, genre, sequels and new games will be clarified. In chapter 3, the methodology of the experiment will be described. In Chapter 4, we will give the results of the statistical analyzation and interpret these results in a discussion and conclusion in Chapter 5.

2. Theoretical Framework

Uncertainty

The prospect theory (Kahneman and Tversky, 1979) states that the preference of decisions with uncertainty is dependent of the circumstances. Therefore is the estimation of chances and risks not objective, but is relative to the previous situation. Consumers are inclined to out more emphasis on potential loss when buying products or services than the possible gains. This explains that perceived risk can be a powerful explanation for consumer’s behavior. So, when purchasing, consumers are often more motivated to avoid mistakes than to maximize the utility. The feeling of sacrifice has a negative influence on the perceived value of a product. Previously, authors stated that the sacrifice was the price of a product, but it includes much more than simply the monetary value. Snoj et al. (2004, 279) say that perceived sacrifice is “about all efforts, risks and insecurities connected to an acquisition and use of a product”.

Subjective or perceived risk is the risk perceived by the consumer and motivates (buying) behavior. Subjective risk is more than just objective risk, since the average consumer does not gain all the information that is available and cannot process and remember all the information and makes it therefore hard to make and accurate assessment. Perceived risk is a well-researched topic, as well from practitioners (Farquhar, 1994) as from academics. Perceived risk has, in the academic world, been applied in many fields, such as banking (Ho and Victor 1994)), apparel catalogue shopping (Jasper and Ouellette, 1994), and dental services (Coleman, 1994). Mitchell (1999) claims that risk perception analysis can be useful in many (marketing) fields, such as targeting, positioning and segmentation. So can people segmented based on their risk-reducing behavior, as we will study in this thesis.

So earlier research on perceived risk was based on the premise that consumers made objective and realistic assessments on both the possible outcomes and the likelihood of these occurring. However, in a case of explorative innovations, it is hard to obtain realistic and useful information. And in the case of introducing new games, quality assessment is hard, since it is an hedonic product. So in the

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15 game industry, it’s simply not possible for consumers to obtain (much) objective, useful information and make realistic assessments. If we then add the relatively high price of a game, the result is that buying a new game give a consumer quite some uncertainty. As Snoj et al., (2004, 284) concludes: “risk is a subjective estimation by consumers connected with possible consequences of wrong decisions, a possibility the product will not offer all its expected benefits”.

Willingness to pay

Willingness to pay (WTP) is the actual amount of money a consumer is willing to spend on a specific product or service (Cameron and James 1987; Krishna 1991). WTP is a manner to measure the customer satisfaction. If customers are satisfied with a product, they are probably have the tendency to pay more for a product than customers who are not satisfied with the product or service. For companies, the WTP is important, because it gives an indication for the price of a product and on that basis you can design the optimal pricing schedule. Price is an important part of the profit of the product. Homburg, Koschate & Hoyer (2005) explain WTP as “a measure of the value that a person assigns to a consumption or usage experience in monetary units”. Willingness to pay is a measure of the subjective value the customer assigns to a specific quantity. There has been a lot of research on the factors that can increase the consumer’s WTP. Examples of those factors are perceived product quality, brand image, awareness and loyalty (Anselmsson, Vestman Bondesson, & Johansson 2014).

Purchase Intent

Purchase intent (PI) is a measure if the customer has the actual aim of buying the product. It is the plan to purchase a product or service in the future. Assael (1995) states that purchase intention can be used to forecast what kind of brand a customer will buy. Purchase behavior is influenced by affective as well as cognitive elements. This means that consumers make the decision to buy products or services with rational and emotional arguments (Li, Monroe, and Chan 1994). This does not mean that those decisions are made fully conscious, consumers are mostly unaware of their arguments.

Price is one of the most important factors on the decision to purchase a product. On one hand, a high price can have a negative influence on the purchase intention (Grewal,Krishnan, Baker, Borin; 1998)

Since it is of influence on the consumer’s budget and in classical economic theory, price is seen as sacrifice for consumers. On the other hand, a high price can give an indication of high quality (Monroe and Krishnan, 1985). The perceived price is one of the most important factors during the purchase decision process (Chiang & Shawn Jang, 2007).

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16 For this study, it is important to know if respondents would buy the game in the first place. If so, then we can ask the amount they would like to pay. If the purchase intention is low, the probability that the WTP is low either.

Hypothesis 1: The more the customer knows what to expect from a game, the higher the Purchase Intention and the Willingness to pay is.

Game Industry

In many studies, creative industries, cultural industries and game industries are seen as similar concepts. Cultural industries are the industries that include with the creation, production, marketing and distribution of cultural goods. Hirsch (1972, pp. 641-642) defines cultural goods as

“’non-material’ goods directed at a public of consumers for whom they generally serve an aesthetic or expressive, rather than clearly utilitarian function”. Creative industries, according to the Creative Industries Task Force Mapping Document (CITF (2001), as cited in Cunningham 2002, pp. 54) are “activities which have their origin in individual creativity, skill and talent and which have the potential for wealth and job creation through generation and exploitation of intellectual property”. According to Tschang (2007) the game industry is similar to other industries in a number of ways. For example, games require their designers (also known as developers) a considerable amounts of creative thinking. Besides that, games also need to satisfy the consumers’ ever-changing tastes and expectations.

The game industry exists of 3 main players: the independent studios, publishers, and consumers. The studios are responsible for the creative work, such as designing and developing a game. Publishers are responsible for everything else, such as the distribution, finance and the marketing of a game. Publishers do also start their own studios, in order to control their own products. Consumers influence the publishers and developers by reviews and of course the sales of a game.

Previously, console makers produced consoles with the same architecture every time instead on focusing on improving processing power. Examples are improving the console by upscaling the HDD possibilities or adding new peripherals, such as games in HD quality or adding the motion sensing input device Kinect on Xbox 360 and One. But that is now over. Big game console companies are adding extra CPU and GPU power in order to process virtual reality and 4K screens (Playstation 4 Neo) and Xbox One is likely to become more compatible with PC’s so it can run the Universal Windows Platform on the Xbox. Competition among different platforms and the growth of smartphone-based games can put pressure on the performance. The game industry for solely the

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17 smartphones is very profitable (global revenue in 2016 is 12.1 billion dollars3_{). Marchand and}

Hennig-Thurau (2013) created a conceptual framework that “reflects the emerging roles of the highly dynamic video game industry and features both key players and products” (142).

Figure 2: Marchand &Hennig-Thurau’s (2013) conceptual framework of the game industry

The vertical path in this framework is the so called gaming environment, which includes content providers (also called ‘studios’, such as Electronic Arts), game platforms (console makers such as Sony) and consumers. The horizontal path shows the communication and distribution channels that connects the content providers and platform manufacturers with the consumers. This framework acknowledges other institutions besides the game console manufacturers which have influence on the creation of value of games. The lowest 3 circles of the framework shows the influence of the consumer and the recommendations of other consumers, experts or automated recommendation systems on the gaming industry.

Competing in cultural industries is quite a challenge, due to the combination of dynamism and ambiguity. Part of these aspects are caused by the fact that the products in the cultural industry are hedonic goods, and not serve a utilitarian purpose. Hirsch (1972) defines cultural goods as “’non-material’ goods direct at a public of consumers for whom they generally serve as an aesthetic or expressive, rather than clearly utilitarian function” (cited from Lampel, Lant & Shamsie 2000, p. 263.

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18 Instead of having a clear functions, these goods are valued based on subjective experience. It hard to predict on beforehand whether someone likes a game or not, this makes it difficult to predict the success of a game. On the consumer-side, it is hard to predict whether they like the game or not, it is hard to establish clear standards of quality (Bjokergren 1996, Holbrook and Hirschman 1982, Lewis 1990).

Importance of innovation new games

The supply of game products exists of two components: the hardware and the software. The hardware are the actual consoles, the video game systems such as the Wii, the Sony PlayStation or Mircosoft’s Xbox. Software, the actual games, can only be played on one of those consoles for which they are designed. This makes it hard to determine the demand for video games, since this two-sided nature of the market. This is because you only can play a game which is especially designed for example the Playstation, and therefore are the sales of the games limited to the sold amount of the hardware on which the game is released. Clements & Ohashi (2005) even claim that there is a network effect between the hardware and software of games. This effect purports that the sale of the one influences the other. If you have a console where a lot of games are available for, more people will buy that console instead of another kind of console (assuming that there are less games available for other consoles). As the number of hardware units sold to the consumer gets larger, game developers and publishers are willing to make more games to that specific console, since the chances are bigger that they sell more games for this console. This creates a continuous cycle, where consumers buy the console for more games and game developers will release more titles for more sales. This is lucrative for both the consumers (more games) and the developers (more sales). The console game industry is characterized by an oligopolistic nature due to incompatible hardware. This means that the purchase of a game console is a considerable expense for a consumer, because the purchase of a certain game box excludes games from other game boxes. According to Williams (2002) “This non-interoperability created a standard-based industry in which there is only room for a small number of firms”. This means that since the mid-1990s, Sony, Microsoft and Nintendo are the main players of the game console market. According to Zahra (1993) it is especially important for those kind of incumbent firms to be engaged in exploratory behavior, because they are traditionally risk-averse.

Competitive advantages in the cultural and creative industries are driven by novelty and innovation (Williams 2002 and Lampel et al. 2000). While consumers expect a certain kind of novelty in their product, at the same time they crave for familiarity. This contradiction puts producers in the middle of two opposite forces. This results in producers seeking novelty that differentiates their product,

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19 but at the same time not making it to fundamentally different. Lampel et al. (2000, p. 266) state:: This novelty represents a recombination of existing elements and styles that differentiates, but does not break existing artistic and aesthetic conventions. On the other hand, there is kind of novelty that break boundaries. This kind of innovation explores new products, introduces new cultural markets and introduce new technology

Importance of new products refers to “the weight an industry assigned to the value of new products for creating and retaining a competitive position” (Zahra, 1993, 323). In some industries, such as the game industry, new products are seen as a source of competitive advantage. This means companies in the game industry will invest in research, new products development and the introduction of those new products. These firms engage in exploratory behavior, but do not have the urge to explore new markets, since they invest and have invested already that much in the market they already in.

A considerable amount of research has been done about which focus on innovation a company should have: an exploratory of exploitative view on organizational learning (March, 1991; Lewin, Long & Caroll, 1999). According to March (1991) ‘exploration’ and ‘exploitation’ are two

fundamentally different learning activities, in which an organization has to choose and therefore align its internal resources for one of those two. Baum, Li and Usher (2000, 768) defined exploitation as the “learning gained via local search, experiential refinement, selection and reuse of existing routines”, and exploration as “the learning gained through processes of converted variation, planned experimentation and play”. Research has shown that a combination of these 2 activities is the most successful one (Raisch and Birkenshaw (2008) and Levinthal & March (1993). Combining these activities is called ambidexterity. Raisch and Birkenshaw (2008) define ambidexterity as ‘an organization’s ability to be aligned and efficient in its management of today’s business demands while simultaneously being adaptive to changes in the environment’(375). So companies should have a long term and a short term focus on innovation. By improving the operational effectiveness (and having a exploitative view), such as making products faster and cheaper, a company gains a competitive advantage on the short term. But other companies are also trying to improve their productivity, which eventually will result in lower product prices and lower profit margins for all companies. Therefore a company should also focus on the long term by investing on research and development of new products, services or markets.

Cadin & Guéring (2006) state that the creative industries are not particularly fond of revolutionary innovations. They often slightly renew genre that were successful for a longer period of time (Lampel et al. (2000).By using the definition of explorative behavior of Benner and Tushman (2003), entering

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20 a new market can be seen as exploratory innovation. Situmeang et al. (2016) states that

technological exploration is even essential in order to survive in technological driven markets: ‘…firms have to innovate in order to keep up with the increased processing power and capabilities of console hardware to create realistic in-game models (23)’. Entry to a new market is a risk-taking activity. Organizations in general tend to avoid such activities unless there is a strong urgency to do so with respect to their survivability.

Nowadays, firms have to keep up with the constantly improving technologic capabilities and raising processing power for better and more realistic performance of the consoles. Therefore, they continue to innovate and innovation is more a necessity in order to survive in this industry.

Situmeang, Gemser, and Wijnberg (2016) already wondered why a firm makes the decision to “enter a market segment that is new to them while their environment is already fraught with risk due to rapid technological changes” (23). Although entering a new market has definitely a positive side: it can mean new opportunities for a firm and it can diversify its operations and thereby spreading the risk. However, like most explorative ventures, the outcomes are very uncertain and only noticeable in the far future.

Hypothesis 4: The customer’s individual perception to uncertainty is a negative predictor on the willingness to pay and purchase intentions on totally new games

Incremental Innovation

As mentioned earlier, it is hard for game companies to predict which kind of game will sell well and which games are a failure. Since games are experience products, the opinions about games can diverge, which makes it even more unclear to predict the success of a game. One thing is sure, consumers like familiar elements in a game, combined with new elements. Lampel, Lant & Shamsie (2000, pp. 264) states that “consumers need familiarity to understand what they are offered, but they novelty to enjoy it”. Tschang (2007) claims that the typical consumer instead of buying a game that combines genres prefer to buy a game within a genre.

Tschang (2007) developed a framework to see the possibilities game companies have in order to answer to the opposing pressures. He defines 3 different strategies a game company can follow. First, when introducing a new genre, which is a radical innovation, is a hit, it is unlikely that the company will follow up with another new radical innovation. It is much easier, and therefore cheaper, to make an incrementally innovative game or a sequel. An example is the Sims4_{, which was}

followed up by many expansion packs and eventually the Sims 2 was introduced. If the new game is

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21 not hit, the developer will continue to improve and refine the game.

With the second strategy, the first product is also an radical innovation, but within the same genre. Also in this case, if the first product is a hit, probably an incremental innovative game will follow. Especially if the developer has introduced valuable Intellectual Property (IP) in the first game, this will exploited in the follow-up. If the performance of the first game is below expectations, the game will be modified and might implement a less risky application of its innovation.

The last strategy starts, contrary to the other 2 strategies, with an incremental innovative gameplay. If this is a hit, or if the sales are reasonable, the developers can develop an incremental innovative follow-up. These strategy will probably have less success and revenue as the other 2 strategies, but a studio adopting this strategy might outlive financial hard times and wait until they are in a position again to innovate to a greater extent later.

The unpredictability about whether consumers like the new games or not (especially the games with new forms of gameplay), combined with the growing product complexity, create major uncertainty.

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22 The process of novelty in minor differences through product differentiation, is called rationalization. Rationalization is defined by Tschang (2007, p. 989) as “the predominant focus on business interests or productivity-oriented production processes, usually at the expense of creativity”. Rationalization can be compared to the exploitation side of the game industry. In the creative industries,

economical and/rational interests are constraints to the creativity of the developers. There will be less space of spontaneous discoveries and abrupt acts.

Even though Tschang’s (2007) framework suggests that the adaption is done between different games; game developers often adapt and tune games while their already on the market. This can be done for incrementally as radical innovative games. In this way they can even respond to uncertainty (i.e. not knowing if the consumer like the product) and adapt the product to the wishes of the market place. Tschang’s (2007) framework shows how game developers handle and respond to the creative-rationalization tensions.

Tschang (2007) links the rationalization-creativity tensions of game developers to the explorative and exploitative process, as described by March (1991). March (1991) also emphasizes the

combination of exploiting known process and exploring new opportunities, in order to increase the liability of performance. Although there have been lots of research on the organizational level (March, 1991; Raisch and Birkenshaw, 2008), Tschang (2007) and Lampel et al. (2000) illustrates that the exploration-exploitation pressures take place at multiple levels and across different actors, such as in the creative industries.

Sequels

One emergent trend in the video game industry is the popularity of sequels or games based on licenses (franchises). Since games are very costly to develop and the chance of failure is significant, publishers are less willing to take risks. Knowing a certain film, comic book or a previous game was successful, gives an indication of the sales of the new game. Publishers can simply look at previous sales charts. Consequences are that there is a lack of innovation in the new games, which is also called incremental innovation. For game producers it is extremely important to sell these kind of games in order to stay viable in such a dynamic and competitive market. Sacranie (2010) studied the influence of sequels on the sales numbers, but there was no significant effect found. The reason for this outcome can be, according to Sacranie (2010, p. 52) “that licensed-based games do not sell huge numbers, but these games are cheap enough to produce that they are able to sell enough copies for the producer to secure an easy profit”. For sequels, It is possible that game producers simply want to reduce the risk, says Sacranie (2010), and not expect huge sales figures. With the sale of sequels and

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23 franchises, game producers can stay stable and allow them to take risks in the future, once

production costs are not so immense anymore.

Releasing sequels are according to Henig-Thurau et al. (2009) for film companies less risky than introducing an original movie. The sequels generate higher revenues compared to non-sequels. Even though Henig-Thurau et al. (2009) conducted their research in the film industry, they believe that these results are also applicable on the video game industry. Sacranie (2010) states that sequels are risk-averse and that game publishers are less willing to take risks.

Hypothesis 2: The customer’s individual perception to uncertainty is positive predictor on the willingness to pay and purchase intentions on video game sequels?

Genre

According to Tschang (2007) a genre can be uniquely defined by a different composition of

elements. Generally, these are forms of gameplay. Gameplay is defined as (Salen and Zimmerman, 2003, p.303) “the formalized interaction that occurs when players follow the rules of a game and experience its system through play”. Distinctions can be made on the particular visual style (such as Photorealism, where a game is as real as possible), genre-specific stories or background (such as fantasy). Tschang (2007) states that gameplay is the main factor of a game’s distinctiveness, since The game’s design generally encapsulates all these aspects (with gameplay following from the game’s design) (p. 991). Henderson and Clark (1990) claim that a new genre can be seen as a radical innovation, but there is no consensus about this. New genres can also been seen as an incremental innovation, since new games often extend a genre by imitating various elements, such as visual styles, forms of gameplay of story. Means to integrate these elements can be seen as an incremental innovation of an existing genre. So incremental innovation essentially expand a genre and does not create major changes in the gameplay. That’s why introduction into a new genre can be as

something between an incremental and an radical innovation.

Game producers are having a hard time meet the consumer’s wishes. Not only do they demand for novelty, and at the same time creativity; for most consumers, games are highly substitutable. Especially in genres which are oversaturated, such as first person shooters. There is a big chance your game will not be noticed in the huge pile of games in the same genre. Last, consumer’s taste is also highly versatile. It is therefore not very strange that game developers and publishers are having a hard time to decide what kind of game to make. So, the choice of genre for a publisher is of influence on the sales of a game, but it’s unclear on beforehand which way it influences the sales. Sacranie’s (2010) study showed, however, that most of the genres games were in, were not

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24 significantly of influence on the sales. Only games in the action (non-first person shooter) genre sold significantly better than other genres. According to Sacranie (2010), one important factor for the demand of games is genre. Every consumer has a different taste for games, some like a specific gameplay or a high playability5_{. There is evidence that genres are of influence on game sales. Taste}

of consumers are constantly changing, which makes it hard to measure if a game being in a specific genre is of influence on sales. So, it is hard to predict that, for example, games in the Fantasy-genre are selling better than action games. In addition, some genres are oversaturated, meaning that there are too many titles in de same genre. Although the consumers wants some familiarity, they also crave for a variety in the market offerings. Sacranie (2010) gives an example of releasing an unique game in an underrepresented genre can be very successful: the release of Guitar Hero in the poorly performing music genre in 2005. Situmeang et al. (2016) say, that entering into a new genre is an risk-taking, explorative activity, since you’ll be entering a new market segment. After all, game genres are often correlated with market segments (Greenberg et al. (2010).

Genre is an important indicator for consumers for what to expect from a game. Video games of certain genres share the same characteristics, such as rules, visuals, and storytelling. These characteristics form the basis for the consumer’s expectations, which is different for each genre (Hsu, 2006). Greenberg et al. (2010) state that consumers who prefer specific genres often share the same features, such as age, gender and personal traits. Genre therefore represents different market segments.

Genre is also called the operationalization of taste (Hsu, 2006) in the experiential industries. Austin’s study (1988) showed that the genre of a film is the most important reason for audience to go to a certain film.

Hypothesis 3: The customer’s individual perception to uncertainty is a predictor on the willingness to pay and purchase intentions on games in new genres

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3. Methodology

This section will discuss the methodology used to answer the research question. First, we will discuss the research design, then the survey used in this research. After that we will explain how the data was collected and finally, the statistical analysis is explained.

Purpose of this research

This research aims to analyze the effect of Uncertainty Avoidance on the willingness to pay and purchase intentions in the game industry. Willingness to Pay and purchase intentions are further specified by the kind of game: a sequel, a game in a different genre, or new game. Also the

respondents’ characteristics were tested to see if they are of influence on both dependent variables. In theory, the more uncertain a person a, the more that person tend to buy something that is as familiar as possible. In this research is that the sequel. At the opposite, someone who scores low on Uncertainty Avoidance and is therefore a certain person, tends to favor new games. This study clarifies whether a person’s need for certainty can be carried out in their buying behavior. The results can work through to marketing activities in experiential goods, where focus on ‘new’ parts of games can be shifted to familiar parts of the game.

Data collection and methodology

Data Collection

In order to test the influence of Uncertainty Avoidance on willingness to pay, a survey was distributed. Within the survey, there was an experiment. An experiment was chosen for this research, so that different consumers could grade the same products (a game) with small

differences. Besides that, responses of the respondents could be compared. With the information from this survey and experiment, a statistical analysis was executed.

The survey was distributed online, among friends and acquaintances of the researcher. A benefit of an online survey, is that it can be distributed easily to different places. The survey was also placed at different game forums, such as Reddit6_{, so that the sample group would be more diverse. In}

addition, an online survey also lower the costs, needed less time to set up, and the answers can be collected simply. There are also a few disadvantages using an online survey. We cannot check if they experiment was conducted seriously by the respondents, or that they may have been distracted of

6_{www.reddit.com}_:_{On Reddit, anyone can create a community on nearly any topic imaginable. Each}

community is independently moderated by volunteer users. Community members can share content including stories, links, and images.

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26 limited in time. The online tool Qualtrics7_{was used to design the survey. After deleting the}

uncomplete questionnaires, the total number of respondents was 68.

In order to test the Uncertainty Avoidance, different statements were posited in the survey. Examples of those statements are:

-I like to know how a movie, book or game will be before I buy it. -It is very important to me to have long term security of employment. -I like to take decisions where I’m not sure about the outcomes.

-I rather deal ad hoc with a situation, than that I prepare myself for many which may never occur. Questions about Uncertainty Avoidance were retrieved from the website of Geert Hofstede8_{and as}

used by Yu, Taylor and Chen (2001).

Choice of games

The participants of this experiment were exposed to 9 different games. These 9 games were divided in 3 different groups. Each group represented one of the game producers (Squere Enix, Microsoft and Nintendo) and was different genre than the other 2 groups. Each game had a description of the game itself and a description of the producer. Further, the logo of the producer was added to the image of the game. The reason that 3 different producers were used, was to exclude the possibility of brand awareness. Besides that, in order to get pass the fact that respondents just don’t like the specific game genre that was picked for them, 2 other game genres were added. So in total, we asked the respondents about their willingness to pay and purchase intention of 9 different games. Each group consisted of 3 games: A sequel, a sequel in a different genre and a totally different game in a different genre. To make sure that respondents knew that the first game was a sequel, words as expansion pack, next chapter and numbers were added to the title and the description.

For this study, information about games was retrieved from metacritic.com. Metacritic gives data about the score, the number of reviews, genre and release data. Metacritic gives also a description of each game. These descriptions were also used for the descriptions of the games in the survey. Only with the games in a different genre, the description of the game was adjusted to the genre where the ‘new’ game was adjusted to.

7_{Qualtrix is an online tool for data collection and analysis.}

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27 The games were picked on the base that they were released in the last 2 years, from 2015 to 2017 and had a high metascore (at least 75) of expert critics, so that there wouldn’t be differences in newness and quality.

Survey set up and measurement scales

The survey contains several types of questions: Likert scale questions, multiple choice questions and open questions. The survey started with demographic questions, such as questions about gender, age, education and income. Furthermore, questions were asked about the overall gaming behavior of the respondents, for example how many a hours a week the respondents spend on gaming. Then, the statements about Uncertainty Avoidance were introduced and respondent could express on a 7-point Likert scale to what extent they agreed with the statements. Last, we asked the respondent to what extend they like several game genres. On the next page, the first 3 games of Microsoft are shown. The first game is Halo 5: Guardians; the sequel. A description of the game and a description of Microsoft is added. Questions are asked about the willingness to buy the game. We also asked the respondents what kind amount they would spend on this game, and what they would spend if the game was a limited edition (including a steel casing and a minifigure). After these questions, 3 more questions were asked about the producer, in this case Microsoft. Questions were if the respondents ever heard of Microsoft and if they have purchased a Microsoft game the last year. The second game on the page is the same game, but in a different genre. Description and title are adjusted in a way that it is clear that this game is in a different genre. For example, the game Final Fantasy XIV:

Stormblood is a role-playing game in a fantasy setting. The adjusted game is called Final Fantasy XIV: Full Speed. In the description it is implied that this game is now a racing game. Same questions about the game were asked as the question from the first games. The third game is a total different game from a different genre than the two first games, but is from the same producer. Again, the same question were asked. The next 2 pages in the survey contained 3 games from Square Enix and 3 games from Nintendo. The full version of the survey can be found in Appendix 1.

To measure the WTP and the PI a direct survey was used, meaning that we directly asked the respondents how much they were willing to spend on the games. This is of advantage for this research, since 3 of the 9 games does not actually exists. It is therefore hard to use actual market transactions, which in many cases is seen as a better, more realistic option to measure WTP and PI. Another benefit is that, with this method, respondents can indicate the real amount of money they would like to pay. With transactions data, you’ll only know that the buyer’s data WTP is as least as high as the price of the product and that the nonbuyer’s WTP was lower than that price

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28 approach may be limited. Since the responses are hypothetical and the respondents know that there is no real economic consequence, there is no stimulus for the respondent to answer the real WTP (Miller and Hofstetter 2003).

Variables

-Dependent-For a firm, the customer’s intention to buy the product and the customer’s willingness to pay a certain price is, besides sales, one of the most important measures of success. The dependent variable Purchase Intention was measured with the statement “Based on the given information, I would buy this game” (1= I strongly agree up to 7= I strongly disagree).

The other dependent variable, Willingness To Pay is measured by the question: “What is the maximum amount you would spend on this game, if it’s a regular versions? “ The participant could fill in any amount they wanted.

The uncertainty about the game is also a dependent variable. It is expected that the uncertainty of the game has a direct influence on the willingness to pay and the purchase intention. This is measured by asking the respondents if they know what to expect from the game. This variable is called EXPEC in SPSS, the program that is used to analyze the data.

- Independent-

The independent variables are the kind of game the participants are faced with. This is to determine the degree of exploration. There are 3 degrees of exploration within the games:

1) New game. This implies that a totally different game from a different genre was used for this questionnaire (P_SEQUEL)

2) New genre. The games in genre category were also showed as a sequel, but the sequel was in a different genre than the first game (P_GENRE)

3) Sequel. In the title and description of the game it was explicitly told that this was sequel (P_SEQUEL)

All above mentioned variables are dummy variables. All respondents answered statements about the above independent variables. After de data collection, I separated the answers and divided it in the 3 variables. You should treat each respondent as three different data points, i.e. sequel, sequel different genre, and completely new games.

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29 - Moderator

The perceived Individual Uncertainty is measured through different statements in the questionnaire, which included the following statements:

- I like to know how a movie, book or game will be before I buy it.

- It is important for me to work in a well-designed job situation where the responsibilities and requirements are clear.

- It is very important for me to have long term security of employment. - As long as you follow the rules, everything will be alright.

- It is very important for me to have as little tension and stress possible in my life.

Through a Cronbach’s Alpha analysis the reliability was measured between these statements and therefore is looked if it was to possible to converge these statements to one variable

UncertaintyAvoidance. Cronbach’s alpha is 0.675. The Cronbach’s Alpha is not optimal, but it is still high enough to converge this group under Uncertainty Avoidance.

-Control-Income: A logical influence on buying behavior is the income of a respondent. If a respondent earns little or nothing, he/she will probably less willing to buy or pay a certain amount for a game.

Especially since a game is an hedonic good and is easy to live without.

Gender is a control variable, since it is known that women often have another preference in games than men have (Greenberg at al., 2010).

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4. Results

Descriptive Statistics

In total, respondents answered (the same) questions about 3 sequels, 3 new gene games and 3 totally different games. Table 1 shows the descriptive Statistics of the variables.

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

Uncertainty Avoidance 558 2,00 6,40 4,6194 1,04865

Expectation Game 576 0 7 3,25 1,528

Purchase Intention 581 1 7 4,66 1,693

Willingness to Pay 515 0 60 17,62 14,855

Quality of the game 581 1 5 2,60 ,892

Valid N (listwise) 489

After this, the descriptive statistics were split in the 3 game categories.

Descriptive Statistics New Gamea

a. P_SEQUEL = No, P_GENRE = No, P_GAME = Yes

Descriptive Statistics Sequelsa

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31 Descriptive Statistics Genrea

a. P_SEQUEL = No, P_GENRE = Yes, P_GAME = No

Hypotheses

Hypothesis 1

The more the customer knows what to expect from a game, the higher the Purchase Intention and the Willingness to pay is.

Before measuring the degree of explorative behavior on the WTP and PI, we first checked if the risk perception of the game is a positive predictor on purchase intention and willingness to pay. This is measured by doing a linear regression.

The model to measure is significant (R=.233, F=28.994 , P < .00). The expectations of the game are a negative predictor of the Willingness to Pay (B = -.233 , P < 0.001). Also to see if the expectation of a game is a predictor for the Purchase Intention was a linear regression executed. The model was significant (R=.399, F-108.778, p <.00) and Expectation is indeed a positive predictor of purchase intent (B=.399, p <.01). Reason for the negative outcomes on WTP is probably that the lower the score is on the statement about the expectation of the game was, the better. So a 1 is a ‘strongly agree’ and a 7 a ‘strongly disagree’ on the statement From the description and picture provided to me, I know what to expect from this game. Since Purchase Intent is measured in the same way, there is a positive relation (the lower the score, the better) and with the Willingness the Pay (the higher the amount, the better) there is a negative relation. So the perceived expectations of the game is a positive predictor on both Purchase Intent and Willingness to Pay. Hypothesis 1 is therefore confirmed.

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Hypothesis 2, 3 & 4

To answer these questions, first the correlations were measured.

As you can in the table below: there are significant relations between Willingness to Pay, Quality of the game, Purchase intention and Game Expectations. So when the consumer knows what to expect is positively correlated with Purchase intention, Quality of the game and the Willingness to Pay. The individual’s perceived uncertainty is not correlated with any other variables.

Also here the negative relationship between Willingness To Pay and the other variables is in fact that Willingness to Pay is measured differently than the other variables. After this, the scales were revered so that for the next analyses there would be no negative relations anymore.

Hypothesis 2: Sequels are the most popular with people who score high on Uncertainty Avoidance

From the table above, we can conclude that perceived uncertainty on itself is not of influence on the

After this, we wanted to see if there are besides correlations also predictors in the results with a regression analysis. To see if the model is fit for analysis, Non-Normed Fit Index (NNFI, also known as TLI), Comparative Fit Index (CFI), and root mean square error of approximation (RMSEA;) were

Correlations Willingness To Pay Game Expectation Purchase Intention Quality Game Perceived Uncertainty

Willingness To Pay Pearson Correlation 1 -,233** _-,457** _-,389** _,034

Sig. (2-tailed) ,000 ,000 ,000 ,448

N 515 508 510 510 491

Game Expectation Pearson Correlation -,233** ₁ _,399** _,473** _-,034

Sig. (2-tailed) ,000 ,000 ,000 ,426

N 508 576 575 574 548

Purchase Intention Pearson Correlation -,457** _,399** ₁ _,461** _,000

Sig. (2-tailed) ,000 ,000 ,000 ,995

N 510 575 581 580 554

Quality Game Pearson Correlation -,389** _,473** _,461** ₁ _-,002

Sig. (2-tailed) ,000 ,000 ,000 ,968 N 510 574 580 581 554 Perceived Uncertainty Pearson Correlation ,034 -,034 ,000 -,002 1 Sig. (2-tailed) ,448 ,426 ,995 ,968 N 491 548 554 554 558

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33 used. Hu and Bentler (1999) suggested that for continuous data—RMSEA < .06, TLI > .95, CFI . > .95, are reasonable cutoff data. The model used for this study has the following indicator scores: CFI=.998, TLI=.984 and the RMSEA (Root Mean Square Error Of Approximation) is .021.

After this, according to Schreiber, Nora, Stage, Barlow, & King (1999), a chi-square test is needed to show that his model is statistically superior to the original model. Results for this model were Chi-square=12.653, Degrees of freedom = 10 and the probability level is .244. In conclusion, the hypothesized model is a good fit to measure the data.

Hypothesis 2: The customer’s individual perception to uncertainty is positive predictor on the willingness to pay and purchase intentions on video game sequels

To see if the perceived uncertainty predictor, an regression analysis was executed.

Sequel is a positive indicator of the expectation of a consumer (Estimate=.412, S.E.=.15, C.R.=2.753, p=.006). Sequel is also a significant positive indicator of the quality of the game (Estimate=.719, S.E.=.085, C.R.=8.473, p=.00). There is no direct effect found between a sequel and the purchase intention as well as between sequel and WTP.

So Hypothesis 2 is confirmed.

Hypothesis 3: The customer’s individual perception to uncertainty is a predictor on the willingness to pay and purchase intentions on games in new genres

It cannot be proven significantly that a game in a different genre is a positive indicator of the expectations. However, genre is an indicator of the quality of a game (Estimate=.486, S.E.=.085, C.R.=5.727, p=.00). The estimate of the sequel on quality is higher (.412) than the of genre (.486), which means that people see a sequel as a better indicator of quality than a genre. A direct relation between genre and Purchase intent is not significant, this also counts for willingness to pay. Hypothesis 3 is rejected.

Hypothesis 4: The customer’s individual perception to uncertainty is a negative predictor on the willingness to pay and purchase intentions on totally new games

Since a totally game is used to make set the 0-hypthesis and is therefore the default. Results have shown that genre is a better predictor for the expectation than a totally new game. Genre and sequels are also better predictors of quality than a totally new game. The estimate of sequel on expectations are higher than the score of genre and game. This means that consumers have higher expectations from sequels than from game and genres.

The influence of customer’s perceived uncertainty on buying behavior in the video game industry