Effects of Community's Monetary Engagement on the Quality of The

Effects of community’s monetary engagement on the quality of the final product

The game development on Kickstarter

MASTER PROJECT THESIS WITHIN: Informatics NUMBER OF CREDITS: 30 PROGRAMME OF STUDY: Information Architecture AUTHORS: Vojciech Sobolevski & Gözde Meydan JÖNKÖPING 05 2021

Master Thesis in Informatics

Title: Effects of community’s monetary engagement on the quality of the final product Authors: V. Sobolevski and G. Meydan Tutors: Ahmad Ghazawneh and Osama Mansour Date: 2021-05-22

Key terms: Platform, crowdfunding, game development, Kickstarter.

Abstract Kickstarter is a relatively new platform that has risen from coordinating a group of friends and like-minded people to finance some niched and highly unique projects, to the platform, where strangers from all around the world, finance the work of their favorite creators in hundreds of thousands or even millions of dollars. The academic literature and general focus of the public was concentrated to find what makes a campaign successful, advantages of the platform and its origins. We, the authors of this paper, believe that Kickstarter is continuously evolving, which raises some new questions, not of its history and use, but rather of its future potential and what happens, when the campaigns are won. We will look into how backers interact with the creators through monetary engagement and if these creators are able to deliver quality products when provided with much more resources. Our focus on the game industry allows us to see if Kickstarter performs well within the market, where big players exist with experience and lots of funding. If Kickstarter’s developers will be able to keep up with the industry leaders, using financing through crowdfunding, the platform might become a serious financial player similar to venture capitalists or angel investors.

Table of Contents

Table of Contents ...... ii 1. Introduction ...... 1 1.1 Problem ...... 2 1.2 Purpose ...... 3 1.3 Research question ...... 3 1.4 Delimitations...... 3 1.5 Definitions ...... 4 2. Literature Review ...... 6 2.1 Video games industry ...... 6 2.2 Crowdfunding ...... 8 3. Theoretical Framework...... 12 3.1 Fixed and Marginal costs in the gaming industry ...... 12 3.2 Network Effect ...... 13 3.3 Porter’s Generic Strategies ...... 15 3.4 Price Discrimination ...... 16 4. Method ...... 18 4.1 Empirical part ...... 18 4.2 Variables of Interest and Data Collection ...... 18 4.3 The Regression Model...... 23 4.4 Other considerations ...... 23 5. Results and Analysis ...... 25 5.1 Regression Results ...... 25 6. Conclusion ...... 32 6.1 Future Research ...... 33 7. Reference list ...... 34 7.1 Books ...... 34 7.2 Articles:...... 34 7.3 Sources on the Internet ...... 37 8. Appendix ...... 41 8.1 Heteroscedasticity Output ...... 41 8.2 Correlations between Rating on Steam and X1 and X2 ...... 41 8.3 Regression Data ...... 42

1. Introduction

In the new millennium, the Internet has changed significantly how the business is managed and became a part of a new trend of not only digitization, but also digitalization. New methods of doing day-to-day activities have substituted the old ones and new products and services emerged in cyberspace. (Panourgias et al., 2014) The excitement for the Internet was huge, which led to overconfidence in Internet companies and the eventual collapse of the stock market, also known as the dot-com bubble. (Brown, 2021)

While big companies rose and fell trying to address the demand for new services that people needed, there were other companies that tried to create platforms for people to come together and communicate problems and solutions. Companies like Uber that connected drivers and people in need of transportation, or Monster.com, the company that helped employers and employees find each other. (Uber, 2021; Monster.com, 2021)

One of the companies that has quite impressively utilized the increasing numbers of Internet users combined with the simplification of digital money transfer was Kickstarter. The company has helped connect people with creators and their ideas, looking to finance their projects through crowdfunding. Since the launch in 2009, Kickstarter has, as of 22 January 2020, allowed 4 742 065 861 dollars to be pledged to different projects, of which 176 388 were successful. 17 326 058 backers have given different amounts of money to the projects that they liked, helping creative people all around the world to pursue their passions. (Kickstarter, 2020)

The platform has many categories: Arts, Comics & Illustration, Design & Tech, Film, Food & Craft, Games, Music and Publishing (Kickstarter, 2020). However, these categories are expanded even further if one looks through the Kickstarter search engine.

While the platform was designed thinking mostly about small and middle enterprises and independent projects, some of the big companies have used the platform as well. They have started their own campaigns to raise awareness about their new products, gather feedback, test the novelty on a small scale, minimize the risk, and save a lot on market research. (Econsultancy, 2020) Despite that, thousands of small companies and creators have found their source of capital on the platform. (Calic & Mosakowski, 2016) Kickstarter helped them not only get the capital needed for the realization of the project, but also it allowed creators to leverage the willingness of their backers to promote it and give valuable feedback (Mollick, 2016).

While success stories of Kickstarter (Forbes, 2016) attracted many people into trying out their luck, there were a few projects that did not make it on the platform. Some projects have failed due to the fact that the product was solving a problem that was not really there or created a product that at best could be used as a joke. A website called Flopstarter was even created to work as a platform for really bad ideas (FastCompany 2018). However, while some projects went under before they could enter the market, some creators were actually able to secure the funding needed for the project and present it to the backers and the public. As one would expect, some projects did not deliver what was promised (Miller, 2019), which raised the question: how does one

measure the success of such endeavors and is there a limitation to the type of projects it can support?

In this paper, we will analyze the category of video game projects that were financed and investigate their success in making a good product that would satisfy the expectations of not only the backers, but also the general public.

1.1 Problem The literature review, provided in the following section, will investigate critical fields of interest for this paper: video game industry and crowdfunding. Both gaming (Ruggill and McAllister, 2001; McDonald et al., 2020) and crowdfunding (Parhankangas, Mason & Landström, 2019) have been quite extensively researched by academics and those outside of academia.

Literature has been focused mostly on how to manage a crowdfunding campaign and succeed in raising the necessary capital (Cecere, 2017; Cha, 2017; Steigenberger,2017; Kappuswamy, 2017). While this knowledge is priceless for the individual developers and creators, we wanted to see what happens after the money is raised, which is something that literature often omits. The questions about the quality of the end products, their reception by non-backers or how financing was used in development are often underrepresented in the literature.

Instead of concentrating on the individual campaigns, we wanted to see what Kickstarter’s potential is in raising capital for different projects and if it can be an alternative for those, who don’t have other sources of financing available. Internet at its core is a communication technology and as nowadays people can easily communicate with the entire world and present their work, crowdfunding might become much bigger than before and is worth investigating.

We have chosen the gaming industry as the research has shown that this particular market is highly competitive and often requires huge capital to enter (Chalk, 2015; Sakellariou, 2020), which should make game development through Kickstarter nearly impossible. The main point of our doubt comes from the fact that the more prominent game publishers enjoy a massive audience and virtually non-existent marginal costs, which means that after incurring the fixed costs of development and marketing, each extra copy comes very cheaply, especially if the copy is sold digitally through platforms such as Steam. This seems to suggest that if a company is able to access a lot of customers, it can incur enormous costs in development, while charging low prices. Most often, the standard version of a game comes at 60-70 euros at its release, while the game itself could have cost tens of millions to create (Yan Huang and Gilbert, 2018). The question is, when Kickstarter backer, gives a potential game developer 60 euros, what kind of game he will expect, taking into account that due to a low market reach, the developer might work with as little as one million dollars, even though the customer might expect the quality and scope of the game similar to that of the big developers.

To sum up, we try to look into what happens, when the money is raised. As old projects become successful, new ones, in turn, become more extensive and more ambitious. Kickstarter must prove that it is able to handle projects that raise hundreds of thousands

or even millions, if it wants to become a new player in financial markets and an innovation hub.

1.2 Purpose The paper's main objective is to present how community’s monetary support translates into a quality product within the gaming industry. For the purposes of context and introducing relevant factors, we also quite extensively research the platform, discuss its degree of success in financing gaming projects, and the dynamics of industry in question. Despite humble beginnings, Kickstarter has already created a wide variety of games and some creators have ambitions to produce content that can rival the industry giants like Ubisoft or Rockstar Games (Kickstarter, 2020). Our thesis will try to investigate if these ambitions have the potential to be realized.

1.3 Research question The key question that is driving the thesis is:

How do monetary resources, provided within crowdfunding platforms, affect the quality of games?

The question tackles these main issues:

1. How does the size of the project affect the quality of results? 2. Does a higher number of people help in creating a better game? 3. Is it better to have a small, committed community, or larger, but dispersed? 4. If developers have bigger budgets than expected, can they utilize it properly?

These issues are tackled in the model, which will try to explore if Kickstarter developers are able to manage projects that are big and complex. The platform has proven many times that it can raise quite substantial capital, but only the continuous success of the projects that raised it, can ensure that the public will keep donating.

1.4 Delimitations The research will be limited to the games that are published on Steam. This means only the games fully financed during their Kickstarter campaigns and accepted by Steam to be published on their platform, which could take away a lot of games that would not be fully completed or considered problematic by the Steam selection process. The games that did not apply to be a part of the Steam shop, will not make it into the sample either, since other digital stores like GOG or Epic Games were not included. (GOG 2021; Epic Games 2021)

The limitations of using only one store is chosen purposefully to ensure homogeneity in the sample, since rating systems differ from each store. In addition, if the game does not have enough participation to be rated (Steam does not provide a rating for the game if there are not enough people writing the reviews), it will be omitted from the sample.

Finally, the correlations tested in the paper are restricted only to PC gaming. The outcome of this hypothesis might not be applicable to other categories or even to other types of games developed on Kickstarter (like board games or mobile applications). The

focus of this paper is to investigate a very particular phenomenon in a relatively new industry. All conclusions must be interpreted taking this into account.

1.5 Definitions Crowdfunding - “Crowdfunding acts as a new channel for organizations and individuals to receive funding from a pool of individuals for different types of projects” (Nucciarelli et al., 2017). “Crowdfunding is a way of democratizing access to the capital required to commercialize and distribute innovations” (Mollick and Robb, 2016).

Backers - People who donate funds to support the project (Mollick, 2013).

Steam - “Steam is the ultimate destination for playing, discussing, and creating games” (Steam, 2021).

Kickstarter - The name of the platform “where creators share new visions for creative work with the communities that will come together to fund them” (Kickstarter, 2020).

DLC - “It’s additional digital content a player can install on top of a complete video game” (Vicente, 2020).

Product development - “The overall process of strategy, organization, concept generation, product and marketing plan creation and evaluation, and commercialization of a new product” (Entrepreneur, n.d).

Multiplayer games - The game that players play online over the Internet (Morgan, 2009).

Indie games - This indicates “the game made by one person or a small team, especially one without financial support from a publisher” (Gamedesigning, n.d).

Game engines - “The software that interacts with the hardware of the platform on which the game will be played, to help realize novel, game-playing experiences” (Panaurgias et al., 2013).

AAA games (pronounced “Triple-A”) - AAA games are large budget games which are developed and published by large teams (Vicente, 2020).

Loot box - Loot Boxes help players to “purchase — with real money — to obtain virtual weapons, unique digital outfits, for “skins,” and other goodies” (Lazarus, 2020).

In-game purchases - “In-game purchases are new content, game functionality, features and/or upgrades for a particular game or app are offered during gameplay” (Pegi, n.d).

Pay-to-win - “It allows players to purchase items or abilities (e.g., more powerful weapons, additional health points) that give them an advantage in the game” (Cyberdefinitions, n.d).

Survivorship bias - “Survivorship bias or survivor bias is the tendency to view the performance of existing stocks or funds in the market as a representative, comprehensive sample without regarding those that have gone bust” (Chen, 2020)

2. Literature Review

2.1 Video games industry As gaming has surpassed Hollywood as the biggest industry in entertainment, a lot of creators wanted to participate in the market with their own products. (Econotimes 2019) The phenomenon that is worth looking deeper into, is that the industry itself is highly segregated by the level of differentiation of products.

Some games like “Undertale” or “Five Nights at Freddy’s” are developed by small teams or even one person and can attract a lot of attention (Schilling, 2018; Groux, 2016). Meanwhile, games like “Witcher 3” or “Grand Theft Auto 5” are developed by studios that have invested millions of dollars into the development of their games and hired a very expensive workforce to do so (Chalk, 2015; Sakellariou, 2020). The market’s dynamics and structure have been developing throughout many decades and can be better understood, by analyzing its history.

The videogame industry has developed in a way that most industries have. Highly inefficient markets, at first, were transformed into an industry as demand increased and big corporate players entered. Today, the video game industry draws attention with its tremendous growth rate and opportunities (Williams, 2002). However, it was not always as big as it is today. The first video game was produced in 1958 (Williams, 2002) and in 1971, "Galaxy Game'' was released as the first coin-operated game (Zackariasson and Wilson, 2012). Due to the size of the market, the first games developed were not used in commercial transactions between suppliers and consumers, as they are now (Zackariasson and Wilson, 2012). Only towards the end of the 20th century, video games emerged as a media form that increased their popularity by pushing technological and artistic boundaries (Wood and Carter, 2018; McDonald et al., 2020). At the beginning of the new millennium, the gaming industry did indeed attract attention with a growth rate of 15% from 1998 to 2001 (Williams, 2002)

According to Zackariasson and Wilson (2012), video games can be considered a nearly 40-year-old industry, despite that, the gaming market has expanded very quickly. New games and game systems were launched after the first games were used in commercial transactions (Wolf, 2012). Systems such as Atari, Xbox and PlayStation, among others, found their way into the homes of average consumers. As consoles and games for them were developing, the gaming industry on Professional Computers was developing simultaneously.

At first, since personal computers were still rare and their capabilities very limited, games were mostly created by small independent creators, who would often do it as a hobby or as a part of serving a niche market. However, as time went by, new personal computers have been developed for use at home and due to the expansion of this technology, the market for games expanded as well. A great example of this is Quicksilva, the company that became one of the first game developers with a full-time staff that could be supported through games' sales. As companies, who had people full- time developing games, entered the market, the industry itself shifted to big project games with huge budgets and a substantial number of employees. (Mark Eyles, 2016).

Besides dominating the marketplace, the big players were endowed with certain advantages that put them in the league of their own. A great example is the market for multiplayer games. According to Graham Morgan (2009), online games have more considerable engineering challenges than non-online games. The technology used for development is not standardized, which often means that each company must develop its own systems and tools. That implied that small developers do not really have the capabilities to enter the competition.

Another advantage is related to big technological clusters that enjoy spillover effects. In Japan’s city of Fukuoka, for example, despite high labor costs, companies stay there to enjoy an advantage in a skilled workforce and technological capabilities that might not be present elsewhere. They share tools and know-how among the developers to ensure that their cluster can better compete globally in international markets. (Takeaki Wada et al., 2014) Smaller developers would not be able to afford an expensive location or would lack the necessary connections within the industry to benefit from this advantage.

Finally, even after developing a game, one must always consider the hardware that the game will be running on. Platform developers like Sony (PlayStation) or Microsoft (Xbox) must often make choices regarding the quality of their hardware, since platforms with better performance, might raise costs and requirements for game developers, which in turn can discourage a lot of them to build their games for that platform. In the early 2000s, Nintendo Wii was able to get a lot of games developed for their platform, simply because it required lower costs, as Wii had lower performance requirements (E.G. Anderson Jr.. et al., 2014). Game developers, small and big, must always take into account the hardware that customers have. However, while big gaming companies can build for both low- and high-cost platforms, smaller developers cannot tackle the project that requires a high capital investment at the early stage of development. This means that for certain platforms, only big companies can enter the market.

A video game is a complex network of elements that include technology, culture and social networks (Ruggill and McAllister, 2001; McDonald et al., 2020). In addition to that, creativity in the industry is another major factor that often separates winners from losers. This is, where smaller indie developers can outmaneuver their competition. While building an innovative environment is quite challenging, strong financial means do not necessarily translate into better creativity, as there are many things to consider. Sometimes highly skilled people or expensive technical software is not sufficient. For example, Nikiforos S. Panourgias et al. (2014) suggest that creativity is related not exclusively to people or technology, but it exists rather in cooperation between those who create games and the tools available (f.eg. the capabilities of game engines). This synergy has a strong effect on creativity, but it is not guaranteed by simply investing strongly into people or technology.

Independent development might not only serve specific niche markets or compete through creativity, but also help a social cause. With video games, we can create “raising awareness of important social issues, developing gaming literacy in real-life situations, and learning through designing games in a participatory culture” (Rahimi et al., 2020). Due to the absence of a profit motive, most big developers will avoid developing content for social issues. This opens a range of game projects that might not

be very profitable, but might help tackle a certain issue. For example, games might help a disabled child to maintain focus by gamifying the learning process and instead of simply telling a student what to memorize, the person can be involved to a much higher degree through the game. Especially, since the game development might not require a lot of resources if development software or music comes from a free source, while the game itself maintains simple graphics. (Jungmin Kwon, 2012). Despite its small scope, the iterative processes that are used in game development and other techniques widely used in the industry, should still be maintained to achieve maximum quality and efficiency (Tiago Cardoso et al., 2017). For any independent developer, who wants to build a game as a hobby, job or as a contribution to a social cause, there are a lot of things to consider: the game engines that are used to develop the game, hardware it will run on, the competition it will face, creative processes, etc. are all important parts in creating the experience. However, there is one part of the industry, where indie developers, especially those who use Kickstarter, must truly outshine their bigger competitors.

Social media and the company's online presence play a crucial role in determining the project's future success or failure. As Mark B. Houston et al. (2018) described, the consumer activity before the launch can contribute heavily to higher or lower levels of sales. The anticipation, reviews from reputable sources and recognition by the relevant press are all creating a “buzz” that will facilitate a higher purchasing rate, before word of mouth can even spread throughout the market.

For Kickstarter creators, social media and other online platforms do not only help promote the project, but also finance it. Big companies like Sony or Microsoft use social media to interact with their consumers and collect feedback before launching their products (Y. Kim and J. D. Chandler, 2018). The smaller independent developers have found a way to use the community for finance, marketing and even developing purposes, as a constant stream of feedback, comments and suggestions can shape the project’s final form, before its release. The key to understanding this phenomenon is to learn how efficient this new way of developing games actually is.

2.2 Crowdfunding "Crowdfunding has emerged in the past 15 years, quickly becoming a hot topic for research which has generated considerable knowledge” (Parhankangas, Mason & Landström, 2019). To get a better understanding about the potential of Kickstarter, we have turned to literature on crowdfunding to learn the history and practical use of this type of project financing.

“Crowdfunding” refers to individual entrepreneurs or groups, financing their ventures by receiving small financial contributions over the Internet without using standard financial intermediaries in certain time periods” (Parhankangas, Mason & Landström, 2019). It has proven to be a great alternative for raising funds, especially when other sources are not available (Kuppuswamy & Bayus, 2014; Osuala et al., 2018).

Although the popularity of platforms like Kickstarter might seem like a recent phenomenon, according to researchers, the first successful crowdfunding dates back to 1700 (Bretschneider et al., 2014; Kuppuswamy & Bayus, 2015b; Thurridl & Kamleitner, 2016; Zhao, Harris & Lam, 2019). Crowdfunding has been used in arts,

music, political campaigns, charities and local governments (Kuppuswamy & Bayus, 2018; Ordanini et al., 2011; Parhankangas et al., 2019). As the process of digitization moves a lot of things into cyberspace, crowdfunding has also utilized the full potential of the Internet. The first successful online crowdfunding took place in 1997 with a donation collected for the tour of the British rock band Marillion (Parhankangas, Mason & Landström, 2019). After this successful initiative, crowdfunding companies were established in different sectors (Parhankangas, Mason & Landström, 2019).

Many people might recognize the similarities that crowdfunding has to microfinancing, which has gained popularity all over the world, especially in developing countries. While both ways to raise money do allow a struggling entrepreneur to circumnavigate traditional sources of financing (like angel investors or venture capitalists), which might be biased, they are very different types of financing. The critical element that separates microfinancing and crowdfunding is the fact that the former is a type of a loan that is supposed to be paid back with interests, while a person, who raises capital through crowdfunding, does not have the obligations to return it (Riedl, 2013). It represents a kind of venture finance through donations or investment models through "open networks" (Turan, 2015). Despite the inability to earn a return and the possibility of the entrepreneur to con his backers, the vast majority of entrepreneurs do fulfill their obligations and people seem willing to support them. Even though some might be late with delivery, Kickstarter and other crowdfunding platforms have created a reputation of an honest creator that rewards his backers (Mollick, 2014).

Unfortunately, there has been some evidence of people being taken advantage of. Hildebrand (2017) expresses the concern about the lack of regulation that could facilitate a fairer financing process and more honest communication between the actors involved. Every success story attracts more and more attention of both creators and backers, therefore, according to Buttice (2017), the social capital and its benefits in fundraising that are available to bigger creators, are not available to novices and even if social capital is created, it dies over time if no new content is produced.

Social capital, in general, as one would expect, plays a major role in crowdfunding efforts, not only in the West, but also in countries like China. Zheng (2014), who compared crowdfunding campaigns between the US and China, claims that a lot of the same things like a social network, shared meaning between the backers and the creators of the project and obligation to fund others, play a significant role in creation and maintenance of social capital. Nucciarelli (2017), adding to the benefits of social capital, talks about how crowds support the projects not only with their monetary resources, but also technology and market knowledge, making the development of the product much more user-friendly and competitive in comparison to the others.

As one enters the crowdfunding platform, there is a lot of uncertainty on approaching the campaign and what factors contribute to the success of the project. Especially for independent game creators, with limited budgets, it is essential to understand the factors behind every successful financing.

Outside of social capital, there are certain things that one can do, to increase the odds of success. For example, Cecere (2017) argues for the existence of special rewards to separate contributors from non-contributors and that people respond well to rewards that

incentivize prosocial behavior. Cha (2017) factors in the people in development and the skills they have. He argues that teams with relevant prior experience, beautiful animated graphics and a variety of skills within the group (rather than the project being made by just one person) can encourage donations as the probability of success looks much higher in the eyes of the backers. Steigenberger (2017) claimed that the successful niche, the demand that is unfulfilled, is the cause that will find its backers as lack of alternatives can create big enough of the crowd to fund the projects that others did not consider. Finally, one does need to understand the dynamics of crowdfunding. For example, according to Kappuswamy (2017), when the monetary support is approaching the goal, the activity of donors increases, just to die right after the goal is being achieved, making it very difficult to estimate what goal should be in the first place (the goal that is too big, can never gather the needed momentum, while the goal that is too small, might collect too little to flourish fully).

When one starts a crowdfunding campaign, there are individual factors for each industry and goal to consider, as campaigns vary strongly in how they proceed. For example, the music industry depends a lot on the initial fanbase and the genre (Gamble, 2017), while social causes can be affected positively by sustainability goals (Calic, 2016). Finally, a lot of entrepreneurs, even without realizing their goal in monetary form, do enjoy great support from their backers and release the product anyways (da Cruz, 2018).

In 2009, Kickstarter was established to finance video game development (Smith, 2015). In 2013, the amount of money committed by the crowdfunding community to video games increased from $ 1.2 million to $ 57.9 million (Bidaux, 2014; Smith, 2015). According to the estimates made by banks, crowdfunding will be 96 million dollars in the next 25 years (Turan, 2015).

As the term “crowdfunding” reveals, first and foremost, Kickstarter, is the platform to acquire financing. It allows the coordination of huge masses to provide this unusual kind of financing in a safe and easy manner, especially among people, who are not strangers to each other (Younkin, 2016). Moreover, the vibrant community of a project might substantially facilitate user-driven innovation and spillover of ideas. In comparison to traditional product development, the community is active throughout the entire process of fundraising and can participate much more closely in creating new value (Mollick, 2016).

The literature stands to prove that Kickstarter and other crowdfunding platforms, while sounding simple in principle, are extremely complex systems in practice. There are barely any limitations on what the scope and the type of project can be offered to the public, therefore the number of variables to consider, for each type of campaign, is quite extensive. The success of the campaign can be defined in several ways and it is not necessarily done in the monetary terms. As mentioned before, the support of the crowd, participation in development, delivery times and reviews afterward are just a few examples of what defines the successful project. In this paper, we will look into the quality of video games that were created through the platform (by definition, successful campaigns), but instead of looking at the rate of campaigns that made it through, we will look into the reviews they got on Steam, as the proxy for “success”. The literature has shown that both the video game industry and crowdfunding have experienced a substantial increase in popularity only recently. Yet, they have already bloomed from

segmented and inefficient markets, into the industry that might define a new generation of value creators.

3. Theoretical Framework

Before conducting our quantitative research on video games developed through Kickstarter, we would like to present to the reader a section that contains certain selected theories on the processes within the industry of video game development. As there are a few fundamental differences between the market in question and traditional markets for regular goods, we believe that a short introduction to the dynamics of the industry can give a better understanding on what makes the market for video games different and how the actors in the market compete and create value.

3.1 Fixed and Marginal costs in the gaming industry As in any growing industry that does not face regulations or any heavy barriers of entry, the gaming industry is a fierce marketplace. It is one of the biggest reasons why not only a lot of big companies, but also much smaller players, enter it, in hopes of earning a healthy profit from thousands of players all around the world.

To properly understand the market and nuances related to it, it is helpful to look at the cost dynamics of the company that tries to enter the market. In usual situations, while a higher quantity of sales usually brings higher profit, the rising marginal and high variable costs often set a limit at which higher sales go beyond a profit-maximizing quantity (CFA Institute, 2020). Suppose one looks at the manufacturers of cars, where higher production values often mean high fixed costs in new equipment and higher variable costs, as each car costs a lot to manufacture. In that case, one will realize that there is a certain point at which higher sales are not worth it, even if the price might not be affected by the increase in volume. Most markets face this dynamic and this is why it is essential to understand how strongly the gaming market differs from the rest.

If you look at Figure 1, you can see that each game has a high fixed cost. Very often, if a game is big enough, it takes hundreds of people working full-time for a few years, before the first sale ever happens. In more traditional industries, fixed costs increase with the increase in profitability. For example, if we return to the previously mentioned car manufacturing, the new plant and equipment will be purchased only, if the cars produced up to this point, have been profitable. Unfortunately, the gaming industry does not allow for this kind of flexibility. All fixed costs must be incurred, before the first dollar in revenue can be expected.

However, after the game is released, another side of the equation is visible. The marginal cost for each copy is minuscule as a share of total cost per unit. In comparison to other industries, selling 500 copies or 500 000 copies does not increase the marginal cost per copy, since the rate for CDs, packaging and distribution usually remains similar. Moreover, as more and more content is purchased through online stores like Steam, additional copy sold does not increase the marginal cost at all. Steam charges a steady commission for each game they sell and it makes no difference for the cost of a copy, if Steam sells five or a million copies.

The elements of this industry result in a very interesting cost structure that each game creator faces. At low prices, that is the result of hyper-competition in the marketplace, the profits are directly contingent on meeting sales targets. Only after reaching a break-

even point, a company can start earning a return on their investment and while the quantity required to meet all the costs is quite huge (especially for Triple-A games), after the point is reached, the profit potential of the game is virtually unlimited. This implies a high risk-reward ratio that, only confident in their products, producers, are willing to bet on.

Figure 1: Cost structure of a gaming company Figure 2: Kickstart cost structure

To a high extent, Kickstarter eliminates the problem of uncertainty, lowering the risk- reward ratio almost completely to the favor of a producer. The fixed costs are fully financed through the crowdfunding campaign, which leaves only marginal costs to worry about. In addition, as a lot of marginal costs are also funded by the backers, who, through their donations, have often already paid for the costs of the shipping and packaging, as the game makes it to Steam, it makes money from the first copy sold, as Figure 2 presents.

Since the product that was created through Kickstarter, eventually remains the property of the creator, any extra sales result in profit, which makes game development a virtually risk-free endeavor, where, if you secure the financing, the worst-case scenario is that nobody, outside of the backers, will buy the game. This lucrative opportunity has attracted a lot of game developers. However, since nobody will finance 30-300 million dollar projects, the big game development companies have stayed out of Kickstarter, which raises a crucial question on the platform's ability to raise considerable funds and for creators to deliver enough value to justify it.

3.2 Network Effect The network effect is the phenomenon, where the company's and products’ values increase as more people become customers (Kemper, 2010). A great example could be communications. When the telegraph was first introduced, it changed the way people were communicating, allowing a quick transmission of messages across the whole world. However, the value of these technologies could have been fully utilized only after they have been introduced to many places. One or two telegraphs would not be very useful, since there would be only one destination the message could reach to and

other destinations had to be still serviced by mail. However, as the number increased, the telegraph became an amazing tool for communication.

A lot of companies on the Internet, which is a form of communication technology, have seen the strength of network effects. Giants like Google and Facebook would have never reached their heights without utilizing the network effect to its full capacity. If you were recommended to join Facebook, but knew that none of your friends or family members are in it, you would most likely refuse. The same with Google, which became your “go-to” search engine, because of how many people would advertise on Google supporting it financially and designing their websites specifically to be compatible with search engine’s algorithms.

Platforms like Kickstarter thrive on the Network Effect, where its value creation to the backers and creators is directly contingent on the fact that both groups of people would find Kickstarter helpful in facilitating the cooperation to build something new. As every new project is financed and gets good reviews from the backers, new potential creators and backers are more confident to pursue the projects through the platform. When it comes to the website itself, the technology is not very complex to copy and theoretically, thousands of people could have started their own Kickstarters. However, they would not have, what Kickstarter has - a network of backers and creators. Any new platform would have to start from scratch and since creators stand to lose a lot of time and backers - money, they would rather go with someone tested like Kickstarter.

If one analyses deeper the platform's business model, one might find that its goodwill, which was created through the Network Effect, is the key asset in the whole company. If well-maintained and nurtured, the asset could bring excellent returns to the owners and simultaneously easily rival any competition that might try to copy Kickstarter’s success. As the figure shows below, it would take a new competitor a long time and cost to reach profitability. That often is enough to scare off any potential entrepreneur.

Figure 3: The Network Effect

3.3 Porter’s Generic Strategies In continuation to understand the peculiar market of the game industry, we would like to discuss the issue of price and quality of the products that are competing for gamers around the world. A good model that summarizes well the strategies companies pursue, to position themselves in the market, is Porter’s Generic Strategies (Porter, 2004). The model is shown below and is composed of two crucial elements that are of concern to any shopper: price and quality. As quality can often be defined as subjective, since something good or bad often depends on people’s taste, differentiation is a better term to be used. It tells us that even though it is difficult to objectively tell good products from bad ones, customers can often see the difference between them and give their loyalties to the one that fits them best.

Figure 4: Porter’s Generic Strategies

Therefore, depending on the focus that the company is prioritizing, different strategies are developed to enter the marketplace, as the model above shows. The cost of games usually depends on the game and can vary from a few dollars to 60 dollars or above. As some games offer better gameplay characteristics and more gameplay time, they are usually charging more than games that offer 5-15 hours of gameplay. However, what is interesting is that games age extremely quickly. After a certain amount of time, the game developers start lowering their price to a very high degree. One can often see that a game that used to cost 60 dollars ends up costing 10 or even less. While these cost dynamics are a big part of developer’s strategies to maximize revenue from these games, it seems that game developers most often compete through differentiation and not the price. This is especially visible with new games, where almost every game of big enough content is priced 60-70 dollars.

Differentiation is the name of the game in the industry. As the cost model discussed above showed, the quantity of copies sold is usually more important than the price. Therefore, developers try to distinguish themselves from the rest. The biggest players like Ubisoft, Rockstar Games, Cd Project Red, Activision, etc. are often using the strategy of differentiation, targeting a broad audience. Due to the convenience and universal availability of the games they produce, primarily through digital stores, these

companies do not seem to segregate their customers and often try to appeal to all gamers out there.

Smaller companies often shoot for expertise in a genre or providing some other interesting elements. These kinds of games, instead of shining in all aspects, try to find something that they are good at and really bring these qualities to life. Some games will have beautiful graphics, others - a compelling story, however, no game that is developed by a small company, will try to hit all targets at once, since if they do, they would be considered in direct competition with big games and it is a competition, they often fail at. Therefore, they go with focus differentiation by narrowing their target and serving their loyal audience, who will focus on the best parts of the game and often overlook bad things.

Due to the nature of Kickstarter’s model, companies and individual developers often start with a narrow focus and their backers. After financing is secured and the game is developed, they try to appeal to the general public, monetize the project better and find new fans for a possible next project.

3.4 Price Discrimination The theory of price discrimination explains how companies, that have the ability to segment their customers into groups, have a chance to harvest a much larger profit, than by charging everyone the same price (CFA Institute, 2020). The real word examples are plenty and often are associated with discounts for specific groups. Instead of saying that “we will charge you more, because you have more money”, the sentiment is “we will charge you less, because your purchasing power is lower”. Senior, student or children discounts are great examples of price discrimination.

Figure 5: Single price to all Figure 6: Price discrimination

As one can see, comparing figures 5 and 6, the profit from selling 110 units of a particular good for 7 (dollars or any other currency), would yield only 770. In contrast, by discriminating based on customer group, one could sell 40 units for 11 to one group and 130 units for 5 to another. With this, the total revenue would be equal to 440+650=1090. This is a made-up example, but the logic usually remains the same and

if a company is able to implement this kind of discrimination, without making customers angry and preventing resale (those who can buy cheaper, could resale their goods to those, who would have to buy at a much higher rate), their profits can increase substantially.

In the gaming industry, there are a few things that incentivize companies to apply this kind of strategy. First of all, a lot of gamers are unwilling to pay more than 60 euros for the game. These kinds of expectations developed over time and became rigid in the industry. If a producer spikes the game price too much, people might simply avoid buying it altogether (Business Insider, 2018). Because of this (in addition to having virtually no marginal costs), the more prominent game developers are making a bet on the volume rather than the price, to make money. As a way to increase their earnings, companies have realized they can charge extra to the players that enjoy the game more than others and are willing to spend more on the experience it offers. There are two key ways that companies can extract extra cash from the players: In-game purchases and DLCs.

Through the in-game purchases, the player can buy additional in-game items. Some of them, like clothes (skins), are purely cosmetic and do not change the strength balance of the game, while others, like better weapons or skills, can make a player unfairly stronger, punishing non-paying players. If this happens, the game is usually defined as a pay-to-win game and it starts losing a lot of its players as frustrated gamers realize that it is not the skill, but rather the money that makes a winner. Therefore, it is often avoided by big multiplayer games.

Single-player games often focus on DLCs, which is a piece of content that is sold separately. This kind of content can vary from soundtracks and cosmetic improvements, to new levels or even storylines. While price discrimination theory usually talks about selling the same product for a different price, DLCs work in a similar manner. If the game costs 60 euros and there is a DLC that costs 6 euros, it is almost guaranteed that it will not be equivalent to 10% of the game. It is a small improvement that is withheld from the game, often from the first day, so that the player, who likes the game a lot, would buy basically the same content for 72 euros (Base game + 2 DLCs), while charging others 60 euros.

Eventually, some games have started treating DLCs as a way to expand their games and give more value. For example, if the game has 10 levels, after the initial release, the company can decide to keep their original team and instead of working on another game, they would create two more levels and sell them as DLCs. In this way, the game is becoming a substantially better product with a much longer story and the sale of DLCs does not qualify as price discrimination. However, this is rare and due to high development costs and the inability to charge higher prices, despite inflation eradicating the value of major currencies, the companies are trying to come up with a way to charge higher rates. If they can’t, the quality or the length of the game, will suffer eventually.

4. Method

4.1 Empirical part For the empirical part, we have chosen to conduct a quantitative study on game development. Kickstarter has been developing games for quite some time, which means that there is a lot of data that shows, how successful the games were and how well they were received by the public outside of the backer pools. By collecting and analyzing the data available, we can draw inferences about our research question and provide useful information on how the industry of game development on Kickstarter might behave in the future.

4.2 Variables of Interest and Data Collection As the game industry represents a rather high risk-reward ratio, especially in developing AAA games, this kind of investment would usually be reserved for a very specific group of investors or venture capitalists, who make a bet on a more uncertain outcome, expecting it to provide an above-average return. Therefore, it is a very surprising phenomenon to see projects raising hundreds of thousands of dollars for game development from crowdfunding. Moreover, as crowdfunding is often based on patronage, rather than business interest and the ability to harvest a return on investment, the incentive structure for the participants differs a lot. The rewards that Kickstarter backers get is often limited to the amount they invest and sometimes, they invest into the project much more than they are offered in terms of pure material benefit

Despite the obvious lack of reward for the risk taken by the backers, who contribute most, there are quite a lot of projects that have raised a very substantial amount of cash, which raises the interest about Kickstarter’s ability to finance projects that cost a lot. The empirical part of the thesis will look at the correlation between the success rate of the game and the monetary results of the campaign. The goal will be to use statistical tools like a multiple regression model to express the relationship and see if Kickstarter has the potential to become more than a highly niched platform for small projects. The key components of the regression model are:

1. The dollar amount that was pledged to the project - Independent Variable. 2. The overall rating on Steam (How many people have given it a positive review as a percentage of all reviews) - Dependent Variable.

Budget Raised

The dollar amount is the key component of this paper, because it specifically targets the question of the potential of Kickstarter to raise money. The variable is independent, since the causality is rather direct: the money is raised first and the product is developed later. Only after the game is finished and released on Steam, the reviews start accumulating over time to give the score that is the dependent variable in this paper.

The correlation between the money raised and the rating on Steam is the focus of this paper and will be the key to understanding the current and future potential of Kickstarter.

Steam rating

In our opinion, the rating scores on Steam play a crucial role in the success of the game, sales and even the future of the company. The review system is treated very seriously by the community and often can convince or deter the gamer in his decision to make a purchase.

As you can see from the illustration below, the rating system considers all the reviews posted about the game. The review is usually a combination of “positive” and “negative” buttons with written text. When the review is posted, it looks like this:

Illustration 1: The example of the review on Steam.

As you can see, the review shows the rating, the hours played, the text for more specific reasons, why the review was given, and also the name of the player on the left. The gamers, who read the review, can see if the player has played long enough, to be in the position to write a review in the first place and what exactly the problem is.

Sometimes there are games, who are given a bad review for a problem in the game itself. There can be a lag, too high demands on the computer, a level that does not work, etc.. Through the review system, the players can signal to the company that they want some feature improved or eliminated. A great example is the game Assassin's Creed: Unity. The game was released with many technical problems, which caused a wave of negative reviews and complaints. The company, in order to correct for it, has worked to fix the issues and has given a free DLC to the players, as an apology for the disappointment. (Entertainment Weekly, 2014)

As a way to encourage this kind of behavior, Steam has its reviews separated into two categories: All Reviews and Recent Reviews. As you can see from Illustration 2, the Mixed reviews score is the average that was pushed down by the negative reviews written during the release. However, the Recent Reviews can signal that the issues have been resolved and for the players that still want to try the game, or for those, who came

back after many years, it seems that the issue has been deal with and anyone can enjoy the game to the fullest.

As mentioned before, the reviews are split into a few categories from Overwhelmingly Negative to Overwhelmingly Positive. However, for the quantitative analysis, we would like a more specific measure as a proxy for a successful project. Luckily, as one hovers over the review, one can get a percentage of reviews that has been positive (Illustration 3). This provides a very specific measure for each game and helps find a better approximation of success rather than assigning a dummy variable for each category.

There were some games in the dataset that did not have enough reviews on Steam to get a rating. These games were excluded from the dataset.

Illustration 2: The picture from the Steam for Assassin’s Creed: Unity.

Illustration 3: The precise number of positive reviews as a percentage of all.

Additional variables

As the thesis question investigates not only the size of the project, but rather a monetary engagement of the donors in general, we will add three more variables that will expand the regression and add more explanatory capacity to the model:

3. Number of backers (how big the project was in terms of its audience) 4. The average donation per backer (how concentrated the donations were) 5. Goal overshoot (A dummy variable that is equal to 1, if the money raised exceeds the goal, at least by a factor of 2, 0 otherwise).

Number of backers

The number of backers, similarly to the amount of money pledged, is an excellent indicator of whether the project is highly niched or more open to the public. In order for Kickstarter to become a platform that can finance big projects, it must be able to facilitate the coordination of bigger crowds. If the correlation will be negative, the implication is that the higher the number of backers, the lower is the Steam rating. If the correlation is different, the higher number of backers could improve the game development process, through their input and support. We expect the variable to be non- significant, as the number of people should not be as important as cash donations.

It is important to keep in mind that what is considered a high number of backers for Kickstarter developers is very different from what is a high number of customers for the big AAA developers like CD Project Red or Rockstar games. However, if there is no drop in quality for Kickstarter games as they move from 1000 backers to 10,000, maybe there is a chance that if the game would have hundreds of thousands or even millions of backers, the developers could still deliver an excellent game, which would imply that they can compete with most prominent players in the market. The regression results for this variable could provide us with insight into these kinds of dynamics.

Average donation

This variable would show the concentration of donations. Through high concentration (a small group of people would give a very substantial amount of money), one can make inferences about how the niched projects perform on Steam. As the rewards for the backers do not differ that strongly with higher donations, it is often due to a pure interest in the project that people pledge high amounts. A high correlation could mean many different things, depending if it's negative and positive. However, since correlations do not prove causality, one can only guess what the regression will show and the interpretation one can make.

Goal overshoot (a dummy variable)

The last variable in the regression would show how people handle higher-scale projects, even if they did not intend it in the first place. Often, this kind of surprise can change a

project from being small and niched into becoming a much bigger project with higher quality expectations. As our question focuses on the ability of Kickstarter’s developers to work on bigger projects, it is interesting to see how the game develops, if the money raised exceeds its initial goal. As this is a more binary idea, we have decided that if developers raised at least twice as much as they expected, they would have to rethink how they develop the game and it would be curious to see the effect it would have on the future rating. Interestingly enough, developers often have a way to internalize new money in a way that not only would fit well into their schedules, but they would even incentivize backers to give more than necessary by providing additional content as the new milestone is reached (very similar to DLC’s mentioned before). These schedules are called stretch goals. Here are a few examples of this:

Illustration 4-6: Examples of stretch goals.

The stretch goals usually make the game longer and often better (fewer bugs, better graphics, etc.). However, it is still interesting how the new cash is integrated into a project and if the developer with more money, had better results. The regression will show it. However, another interpretation of possible positive correlation is that the initial estimate for the base game could have been too low and extra funding was used not only to bring new features described in stretch goals, but also to improve the base game if the initial estimates of the goal were too low.

4.3 The Regression Model Finally, combining all of our variables into one model, we have the regression that will define the empirical part of the thesis. As explained previously, the regression has one dependent variable and four independent variables. It is a least-squares regression that will utilize the data of 100 most recently published games from Kickstarter. With a considerable number of observations, the regression should be robust and informative.

The model:

Yi = β0 + β1Xi1 + β2Xi2 + β3Xi3 + β4Di4 + εi

Yi = Steam review (expressed as a percentage) β0 = Intercept Xi1 = Budget raised (in USD) Xi2 = Number of backers Xi3 = Average donation (Xi1/ Xi2) Di4 = Goal overshoot (a dummy variable: 1= raised at least twice as much as stated in the goal; 0 = raised enough to continue with the project, but did not raise more than 200% of their initial goal. εi = Error term

The regression will be run with the help of EViews software. After the regression is completed, the tests for Multicollinearity and Heteroscedasticity will be performed to ensure the robustness of the model. In addition, the value of the R-squared will be provided, to comment on how well the model captures the variability of the dependent variable.

The goal of the model is to answer the questions that were raised at the beginning of the thesis. By analyzing community’s monetary engagement, we can see how this engagement affected the quality of the games in the past. This, in turn, can help predict the future successes and failures of game development and tell us what happens as projects increase in popularity, complexity and scale.

The data for the regression model was collected manually and can be found in the Appendix.

4.4 Other considerations

Scatter plots and outliers

While collecting and analyzing data, the paper will provide additional analysis of scatter plots showing the correlations between dependent and independent variables, while also showing correlations between independent variables if that will be relevant. The regression results might imply correlation or lack of it, while often doing so without context. Under a closer consideration of scatter plot, the correlations might be useful in understanding the dynamic between variables, even if variables themselves are not significant and might give some interesting insights about the results of the regression and variables of interest.

Bias

We are aware that due to the nature of our dataset, it will be heavily affected by the survivorship bias. The projects that were not funded well enough or were closed, never made it to Steam. Obviously, if underdeveloped games would be released, they would probably earn a bad rating, changing the results of the regression. However, in our opinion, the fact that only completed games made it into the dataset, has positive implications for this research.

The paper does look at the capabilities of creating big projects and how the financing of these projects affects the quality of the games. The only way to really evaluate the game is by reviewing it at its best. If the dataset included the games that were not complete, that could skew the results, because the comparison would not happen between semi- completed games with good financing and semi-completed games with bad financing, but rather between completed small and underdeveloped big ones, as completing smaller projects is easier than the big ones. That would be comparing apples to oranges and would put small projects at an unfair advantage.

Therefore, the publishing on Steam is the key assumption that will guide how the regression is built. For the observation to make it into the dataset, it must fulfill these criteria:

1. The project has to have a good team of specialists, who can develop the game from start to finish. 2. They must be able to raise the money to fulfill their stated goal. 3. They release on Steam and are able to fulfill all the requirements to do it.

Currency

The projects are sometimes raised in different currencies. Since USD is the most famous currency in projects, if there is another currency, we will change it into USD using the rates that are present at the point, when we record the observation in our dataset. Dataset was collected within a limited timeframe, which should help us avoid any radical movements in exchange rates. All numbers are rounded up to the nearest dollar.

5. Results and Analysis

5.1 Regression Results Dependent Variable: Steam Rating

Constant 0.8171* (0.0377)

Budget Raised (in USD) 7.58x10-8 (6.02x10-8)

Number of Backers -4.14x10-6 (3.57x10-6)

Average donation -0.0020** (0.0001)

Goal overshoot (dummy) 0.0861* (0.0318) R squared 0.1546 Number of observations 100 Note: Standard errors in parenthesis, coefficients are significant at 1%(*), 5%(**) and 10%(***) levels. Table 1: The regression 1 results.

The regression has shown the correlations between Steam Rating and its independent variables that were chosen for the model. The results of the regression are quite optimistic as they are insignificant, which suggests that the higher budgets of the games do not vary with quality, which was one of the main concerns of the thesis. However, before interpreting results, we must conduct tests for heteroscedasticity and multicollinearity, to make sure that regression is robust, and its values are reliable.

Heteroscedasticity

The OLS model assumes Homoscedasticity, which implies that the variance remains relatively constant across the model. If this assumption is violated, the standard errors become unreliable, making any statements on significance prone to error. To test for this, we have used the Breusch-Pagan-Godfrey test. This hypothesis test states Homoskedasticity as its null hypothesis and if we fail to reject it, we can safely conclude that our variance does not violate the OLS assumption. As we ran the test, the output did not allow us to reject the null hypothesis at any significance levels (for the full result of the output, refer to the Appendix).

Multicollinearity

Another concern that can intervene with the accuracy and reliability of the model, is multicollinearity. This phenomenon occurs, when two or more independent variables are correlated with each other. It can cause the variables, subject to multicollinearity, to seem insignificant, despite being highly correlated with dependent variables.

We will run a VIF (variance inflation factor) test to see if multicollinearity is present in our regression. The table below shows a centered VIF for each independent variable of our regression.

Budget Raised 15.40 Number of Backers 14.36 Average donation 1.39 Goal overshoot 1.17 Table 2: VIF values for Regression 1.

As the table shows, the two insignificant variables have very high values for VIF, where the value of 5 is often questionable and 10 or higher is simply unacceptable. As we found these results, we started wondering if our first regression was insignificant due to multicollinearity, as this phenomenon often makes independent variables seem insignificant.

To look into this problem, we have run a scatter plot between these two variables and found that they are strongly correlated.

Figure 7: Scatter plot for X1 and X2.

There is a clear trend line, which shows that as projects become better and better financed, there are more and more people, who are donating. The multicollinearity of this strength could have created the problem of insignificance. Therefore, to test the correlation of these variables, we have run two additional regressions, where one of the variables is omitted.

2) Yi = β0 + β2Xi2 + β3Xi3 + β4Di4 + εi

3) Yi = β0 + β1Xi1 + β3Xi3 + β4Di4 + εi

The first regression, out of the two new ones, has omitted the budget and uses only the number of backers, while the second one, has only the budget raised, while omitting the number of backers. As these variables are highly correlated, the exclusion of one variable can be done without much loss in the robustness of the model.

Before running the regressions, we must make sure that the problem of multicollinearity does not persist anymore, therefore, the tables below show the VIF results for regression 2) and 3). As can be seen, the VIFs are within an acceptable range and the regressions will not suffer from multicollinearity anymore.

Number of backers 1.23

Average donation 1.12 2) Goal overshoot 1.17

Table 3: VIF values for Regression 2.

Budget Raised 1.32

3) Average donation 1.23

Goal overshoot 1.16

Table 4: VIF values for Regression 3.

As Regressions 2 and 3 do not suffer from the issue, we can run the regressions and see if the remaining independent variables are significant or not: 1) Dependent Variable: Steam Rating

Constant 0.7943* (0.0331)

Number of Backers 1.64x10-7 (1.05x10-6)

Average donation -0.0016** (0.0007)

Goal overshoot (dummy) 0.0866* (0.0319) R squared 0.1405 Number of observations 100 Note: Standard errors in parenthesis, Coefficients are significant at 1%(*), 5%(**) and 10%(***) levels.

Table 5: The regression 2 results. 2) Dependent Variable: Steam Rating

Constant 0.7982* (0.0340)

Budget Raised 9.14x10-9 (1.77x10-8)

Average donation -0.0016** (0.0007)

Goal overshoot (dummy) 0.0827** (0.0317) R squared 0.1427 Number of observations 100 Note: Standard errors in parenthesis, Coefficients are significant at 1%(*), 5%(**) and 10%(***) levels. Table 6: The regression 3 results.

As can be seen from the regressions above, in both cases the first two variables (Budget Raised and Number of Backers) remain insignificant, despite multicollinearity not being present. Therefore, we can safely conclude that there is no significant correlation between the quality of the game and the money raised.

Significant variables

However, while the insignificance of the first two variables has put the question on the correlation between the size and success to rest, there were two variables that were in fact significant at 5% and 1% levels. These variables show an interesting dynamic between the backers and creators. It raises and, to some extent, answers, the question of the effect of monetary interaction on the quality of the games being created.

The first variable, which is significant at 5% level, is the size of the average donation. The prediction was that higher donation concentration might in fact have a higher effect on the overall quality of the game. Higher average donation implies more dedication from the backers and more support in the overall process. The literature review has shown that backers often not only give money to the creators, but also knowledge and a higher level of communication of what they want, which should result in better games. Interestingly enough, the coefficient in all three regressions is negative, which implies a negative relationship. To look deeper into it, we have run a scatter plot to see the correlation between Rating on Steam and Average Donation, which is shown below. The correlation might seem like a negative relationship, however, it resembles more a random walk, rather than an actual negative relationship. The concentration in the lower-right corner simply implies that there are a lot of games that score high ratings on Steam (another praise to Kickstarter’s creators), but if one looks at the observations that have 60$ per backer and higher, there are games that are both well-graded and not-so- much. In our opinion, this shows a rather weak correlation between average donation

and quality and it is certainly difficult to make the conclusion that the relationship is negative and that there might be causality to it.

Figure 8: Scatter plot between Steam Rating and Average Donation.

The final variable in our regression is “Goal Overshoot”. This is a dummy variable that separates all observations into two categories: those who raised at least twice as much money as they initially asked for and those who stayed much closer to their initial goal. As we have explained before, all developers in our sample were able to reach their goals and publish their games on Steam. Sometimes, however, we found that projects got twice as much or even more money, than they requested in the first place. In our opinion, it is a strong signal, when the public is willing to give you much more than what you ask for, therefore, it was imperative for us to investigate it further.

The positive coefficient confirms our suspicion that there is a strong difference between those who have to fit within their financial constraints and those who are given more room to breathe with extra financing. The coefficient proves that the difference is quite substantial and on average, a much higher Steam review and quality of the game, can be expected by the games that reach this goal in their financing efforts. It is even more convincing if one looks at the scatter plot between Steam rating and our dummy variable. In Figure 9, there is a clear pattern that while projects, which reached their goals vary from excellent to terrible, the projects that have achieved the extra financing, have a different quality standard. They do not fall below average and perform very well with majority of those projects achieving over 80% positive reviews, which explains the correlation coefficient of more than 0.08, in each regression.

Figure 9: Scatter plot between Steam Rating and Goal Overshoot.

However, when the correlation is established, there is always the question of causality. What exactly caused good results on Steam and strong financial support from the community? In our opinion, there is a certain level of uncertainty about the causality.

On the one hand, it is very possible that, just like we have theorized at the beginning, more money allows to cover unexpected costs and finish the game much better. It is very likely, that the new developers often underestimate the project costs and ask too little. As the literature review has shown us, there are a lot of dynamics involved in crowdfunding and it is very likely that the developers asked too little, in fear, that if they asked too much, they might not be able to raise money at all. As a result, the games that received just the funds that they asked for, were not as well equipped to deal with unforeseen problems and ended up releasing unpolished or even unfinished games that end up getting a rating of 0.5 and below.

On the other hand, the causality might be going a different way. One can argue that the success and failure of each game has been predestined by the team that is building it. As literature showed, the team’s social capital and experience can make or break the campaign, so maybe, the higher financing comes from the quality of developers. We believe that the extra funding, to some extent, could have been received by those, who would have performed well even with poor financing. These people, using their charm, connections and expertise, have attracted extra capital and they used it not to finance unexpected expenditures, but rather to create an additional content or polish what is already created.

Finally, there might be a third variable that connects Steam Rating and Goal overshoot. Perhaps the higher amount of money allowed the company to hire additional team members, or they would quit their job to focus solely on the game, instead of balancing their Kickstarter project with a full- or a part-time job. In that case, it would be more focus or bigger teams that produce better results, rather than money to deal with extra costs. Using regression, one can only prove correlation, while causality can still be only a speculation. However, regardless of the reasons behind it, there is a very strong

correlation with 1% level of significance, that proves at least to the backers, that there is a very strong chance of the good game, if the donations exceed the money required by the factor of two or more. For the developers, however, regardless of how money is used in development, extra financial resources can always improve the situation.

Summary

The regression results have answered the critical questions on how financing affects the general quality of the games released on Kickstarter. While heteroscedasticity was not present in our model, the presence of multicollinearity convinced us to run additional two regressions, to avoid the issue and add robustness to our model. Despite additional measures, the first two variables of the model, Budget Raised and Number of Backers, did not show any significance, which means that one can be optimistic about Kickstarter’s ability to finance both small and big projects. Like the other variables, we also have created scatter plots, which confirm regression results and can be found in the Appendix.

Average donation has shown significant results, but a negative correlation, which was unexpected. After consideration of the scatter plot, we have concluded that, while there is an impression of a weak downward trend, we can, to a certain extent, reject the idea of causality. For us to claim that lower donation concentration leads to better games, we should have much higher number of games with high donation concertation. As the Figure 8 showed, only approximately 10% of projects in the sample, had average donations higher than 60, which in our opinion, is not sufficient to make claims of causality or even speculate on it.

Finally, the dummy variable that represented Goal Overshoot showed significance at 1% and the scatter plot, indicated strongly, that the projects that raised at least twice as much money as initially asked, got much better results in game development. We have discussed what kind of causality this might imply and what it means for both the developers and the backers.

6. Conclusion

The paper has researched how the monetary engagement of the crowd affects the quality of the games being developed. We have looked extensively into the literature on the topics of crowdfunding and game development. After looking throughout history and current trends of these topics, we gained the overall understanding and found the issue that was not covered as much as others. Most of the research on crowdfunding is focused on how to manage and win the campaigns that raise money and the economic aspects of crowdfunding. However, the research often lacks in looking on what happens after the money is received and the development starts, as if winning the campaign is not the means to the end, but the end in itself. We decided to look at how game development correlates with the monetary involvement of the community and what implications it has for Kickstarter in the present and the future.

After the literature review, we have provided the reader with some theoretical background and vocabulary that can help to understand how the gaming industry differs from others and how Kickstarter game development differs from the traditional game development with well-established market players.

The method used in our research involved a quantitative analysis, using a regression model, to find the correlation between our dependent variable and a few explanatory variables. The key variable of interest is Rating on Steam, which was chosen as a proxy for the quality of the game. As a high level of positive reviews can make or break the game, we think it is a highly desirable metric and can be very informative to game developers, who wish to appeal to as large community of gamers as possible. The explanatory variables represented how the community engages with the creators and how their monetary support correlates with the quality of the game.

After collecting the data, we ran regressions to find the answers to the questions raised. As the data has shown, the budget of the game or the number of backers, do not determine game’s quality, showing that while a high budget does not guarantee the perfect score, it does not guarantee a bad one either. Analysis of other variables showed that average donation has some hints of negative correlation with the rating on Steam, but after careful considerations of the scatter plot, we have concluded that it is not enough to claim causality. On the other hand, the goal overshoot dummy variable, which looks at projects that got much more funding than they asked for, was significant at 1% and showed that there might be some kind of causality.

In conclusion, the thesis was able to provide a good understanding on the dynamics behind the community’s monetary engagement. The paper showed that community can trust Kickstarter with both small and big projects, as there is no evidence that Kickstarter game developers are overwhelmed by a big challenge. Moreover, community can often signal its trust through high donations and it will most likely help to improve the game in question, as the regression has shown. This means that Kickstarter has a great potential to fund future projects, which can exceed, in its funding, not only hundreds of thousands, but even millions of dollars. Moreover, it also shows the importance of the public in these new industries, where they play much higher role, instead of just being consumers.

6.1 Future Research Kickstarter is constantly evolving as does the public, that instead of being just a crowd of consumers, it is now actively participating in the production, marketing and distribution of new and innovative products. Future research, just like we have mentioned before, should focus more on what happens after the money is raised. How this money is used, rather than how to raise money, should be the question of the researchers. Our research has proven that, so far, Kickstarter has been able to produce impressive games, even when they have big budgets and even bigger expectations to handle. As this platform only recently has gained such trust of the public, it would be interesting to see a quantitative analysis done in the future, where there will be more projects that raised millions, as most projects still raise only in thousands. Moreover, as we have focused only on the game industry, to keep the research focused, it would be useful to see how other industries, such as board games, art projects or product development, work with big budgets.

Obviously, some successful projects deserve qualitative analyses. For many companies in our dataset, the financing received through crowdfunding opened doors to establish their own companies, so for the thousands of entrepreneurs out there, it might be informative and exciting to read case studies on such companies and their first projects.

Finally, Kickstarter is not the only company out there that raises money through crowdfunding. The idea to raise funds with the public is used extensively throughout the world. Banks operate with the principle, of the crowd giving a loan to promising new projects, while Initial Public Offerings often help companies raise new capital with the promise of high return. As the public is getting more involved in the economic life of the world, crowdfunding might morph into some new phenomenon that is difficult to imagine today. When that happens, it would be interesting to read and learn about it.

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8. Appendix

8.1 Heteroscedasticity Output F-statistic 0.6427 Prob. F (4,95) 0.6334

Obs.*R-squared 2.6347 Prob. Chi-Square (4) 0.6207

Scaled explained SS 2.9409 Prob. Chi-Square (4) 0.5678

8.2 Correlations between Rating on Steam and X1 and X2

8.3 Regression Data Rating on Cash Number of Average Goal Name of the game Steam raised backers donation overshoot Iron Harvest 1920 71% 1298726 16607 78,20 1 Max Gentlemen SB 91% 38405 1818 21,12 1 StarCrossed 94% 12270 316 38,83 0 Lonely Mountains: Downhill 92% 53526 1621 33,02 0 Children of Morta 92% 108938 3427 31,79 0 Gibbous - A Cthulhu Adventure 88% 59034 1929 30,60 0 Bloodstained: Ritual of the Night 95% 5545991 64867 85,50 1 AVARIAvs - Ultrafast Turnbased Combat 60% 31384 338 92,85 0 Guard Duty - Point and Click through Time and Space 89% 5908 322 18,35 1 Fell Seal: Arbiter's Mark 91% 45289 1197 37,84 0 Hypnospace Outlaw 97% 35994 1664 21,63 0 ToeJam and Earl: Back in the Groove 92% 508637 8873 57,32 0 Sunless Skies - the sequel to Sunless Sea 85% 504496 11739 42,98 1 Garden Paws 89% 43853 1361 32,22 1 Desert Child - A Hoverbike Racing RPG 80% 10617 545 19,48 0 Vigilantes 82% 8857 418 21,19 0 Wandersong 97% 21936 989 22,18 0 The Ballad Singer 76% 39832 1186 33,59 0 Pathfinder: Kingmaker 77% 909057 18351 49,54 0 The Bard's Tale IV: Barrows Deep 65% 1519680 33741 45,04 0 The Rabbit and The Owl 94% 14228 636 22,37 1 CHASM 73% 191897 6938 27,66 0 Islands of Nyte: Battle Royale 51% 50571 957 52,84 0 Shape of the World 85% 61024 1198 50,94 0 Die for Valhalla! 72% 7359 321 22,93 0 Monster Prom 92% 38336 1592 24,08 1 Kingdom Come: Deliverance 79% 1475025 35384 41,69 1 Legrand Legacy - Tale of the Fatebounds 68% 59384 1001 59,32 0 InnerSpace 62% 28543 833 34,27 0 Legion TD 2 77% 66487 1160 57,32 0 In the Shadows 88% 10356 599 17,29 0 Caveman Warriors 64% 11205 359 31,21 0 Epic Tavern 68% 68415 1599 42,79 0 All Walls Must Fall - A Tech Noir Tactics Game 68% 43759 1402 31,21 1 Sundered 82% 155564 4681 33,23 1 Iron Tides 76% 25712 464 55,41 0

Children of Zodiarcs 70% 203770 6683 30,49 1 Black The Fall 77% 38688 1669 23,18 0 Planet Nomads 68% 130449 4107 31,76 0 StarCrawlers 84% 100278 3652 27,46 0 Pinstripe - An Adventure Through Hell 90% 106729 3780 28,24 1 Cosmic Star Heroine 90% 132689 6414 20,69 0 Thimbleweed Park 93% 626250 15623 40,09 0 Rain World 89% 63255 3030 20,88 1 Faeria 84% 94008 2631 35,73 0 River City Ransom: Underground 76% 170941 5179 33,01 0 Night in the Woods 94% 209375 7372 28,40 1 Conclave 76% 75885 1375 55,19 0 Hive Jump 71% 58675 1972 29,75 0 Shantae: Half-Genie Hero 91% 776084 18558 41,82 0 The Dwarves 74% 310091 5925 52,34 0 Rogue Wizards RPG 78% 74739 1429 52,30 0 Niche - a genetics survival game 89% 72375 2838 25,50 1 Obduction 78% 1321306 22195 59,53 0 Duelyst 82% 137707 3578 38,49 1 RimWorld 98% 210596 9498 22,17 1 Mighty No. 9 57% 3845170 67226 57,20 1 Anima - Gate of Memories 68% 110664 1574 70,31 0 Boss Monster 62% 149741 5657 26,47 0 LAUD on Planet X 33% 41747 945 44,18 0 Twilight Struggle 87% 391047 6566 59,56 1 Hyper Light Drifter 94% 645158 24150 26,71 1 NightCry 61% 314771 2408 130,72 0 Moon Hunters 79% 140969 6044 23,32 1 Into the Stars 38% 111274 4131 26,94 0 Bear Simulator 84% 100571 3871 25,98 1 SUPERHOT 89% 250798 11626 21,57 1 The Flame in the Flood 74% 251647 7420 33,91 0 Torment: Tides of Numenera 71% 4188927 74405 56,30 1 That Dragon, Cancer 89% 104491 3687 28,34 0 CLANNAD 98% 541161 5819 93,00 1 Hard West 78% 73955 4398 16,82 0 Dragon Fin Soup 60% 119719 4044 29,60 1 Chaos Reborn 75% 210854 5051 41,75 0 Timber and Stone 43% 88577 3368 26,30 0 Pulse 50% 80977 2129 38,04 0 Orion Trail 69% 97801 4062 24,08 0 Armikrog 58% 974578 18126 53,77 0 Jotun: Valhalla Edition 79% 50462 2299 21,95 0

Nevermind 74% 76525 1526 50,15 0 Star Command Galaxies 46% 151806 5613 27,05 0 Skyshine's BEDLAM 57% 166540 5266 31,63 0 STASIS 78% 132523 4298 30,83 0 Satellite Reign 75% 628638 15029 41,83 0 Shadowrun: Hong Kong - Extended Edition 85% 1204726 31497 38,25 1 Fallen: A2P Protocol 32% 75584 803 94,13 0 C-Wars 63% 95574 3348 28,55 1 No Time To Explain 83% 26068 2052 12,70 1 Stonehearth 76% 751920 22844 32,92 1 Massive Chalice 72% 1229015 31774 38,68 0 Catlateral Damage 88% 61944 2519 24,59 0 Sunset 66% 67636 2228 30,36 1 H-Hour: World's Elite 69% 252662 2772 91,15 0 Dex 86% 30647 1930 15,88 1 Chroma Squad 95% 97148 3964 24,51 0 Son of Nor 51% 151175 2244 67,37 0 Hero Generations 48% 46190 2355 19,61 0 Elite Dangerous 76% 2150700 25681 83,75 0 Pillars of Eternity 86% 3986929 73986 53,89 1 Dyscourse 77% 44134 1816 24,30 0