Utrecht, July 2010
How To Get Started; An Exploratory
Research Into The Video Gaming
Industry
By
Almer Veenstra
BSc Bedrijfskunde – Rijksuniversiteit Groningen Student identity number: 1669869
In partial fulfillment of the requirements for the degree of Master of Science
in Innovation management and Strategy
Supervisors:
iii Rijksuniversiteit Groningen faculty of economie and bedrijfskunde
iv
Abstract
Given the fact that selection is of utmost importance to organizations, especially the organizations being selected, it is necessary to know how companies are being selected. Selection theory focuses on the relevant selection system for explaining performance differences (Wijnberg; 2004; Caves; Mol and Wijnberg, 2007). To compete successfully one’s products have to be valued and recognized as valuable. This is the starting point of looking at competitive processes from the perspective of the selection system. The goal of this research is to explore how companies developing experience goods are being selected by focussing on the Dutch video games industry. This research covers the selection criteria and the selection methods that are used by selectors to select game developers. 19 game developers have responded to an online questionnaire and 3 selectors were interviewed. The combination of quantitative and qualitative data showed that pitching is not the most important selection method, 30% of the assignments are acquired by pitching. Intermediary organizations play an important role in selecting game developers. Also, game developers can influence selection by promoting themselves by intermediary organizations as well as possible future selectors.
presentation skills can help in self promotion. Also, follow-up assignments are important as well. For follow-up assignments, game developers should think along and cooperate with selectors. The most important selection criteria are past project performance and technical expertise. Location, having a history, knowing the selectors and certification contests can influence selection.
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Acknowledgements
This paper is written as a master thesis for the MSc BA Strategy & Innovation program at
the University of Groningen. The subject of my research has been assigned by Taskforce Innovatie region Utrecht, a semi-government organization. One of the goals of the organization is to stimulate the growth of the video game industry in the region of Utrecht. I have enjoyed working
this project and have learnt many things. I feel ready for the next step, because I am confident about the knowledge, skills, and competences that I have developed during my student time.
I would like to use this opportunity to thank some persons who have supported me during my graduation project. First, I would like to thank Eva Nieuwdorp who helped me with her impressive knowledge about the video game industry. Furthermore, I would like to thank all the colleagues from the Taskforce Innovatie region Utrecht for their support. The nice place to work that you created stimulated me to work hard and has helped me to fulfill this project. I would also like to express my gratitude to Delano Maccow my university supervisor, who supported and guided
me to fulfill the last part of my study. The way you formulated your feedback and questions stimulated me to rethink and adjust parts of my work without pushing me into a direction. I really appreciated this way of working and it definitely motivated me to take this research to a higher level but more importantly, I have learned many things. Moreover, I am extremely grateful to my parents. Your unlimited amounts of support and trust during the past 25 years have made me to who I am right now. Last but not least, I want to thank Simone who supported me during this research and has always been there for me. Thank you so much!
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Executive summary
Introduction
Given that selection is of utmost importance to organizations, especially the organizations being selected, understanding how firms are being selected and what criteria are used, can create a (competitive) advantage. Researchers acknowledge the importance of selection for explaining performance differences; Selection theory focuses on the relevant selection system for explaining performance differences (Wijnberg; 2004; Caves; Mol and Wijnberg, 2007). However, the selection criteria used for selection remains largely unexplored despite its importance (Watt et al., 2010). Therefore, this study empirically examines the selection methods and selection criteria used by selectors in the Dutch Video games industry by focusing on applied video game developers. The Dutch video games industry is chosen because the role that selectors play in the determination of value is generally more visible in cultural industries than in many other industries (Mol and Wijnberg, 2007). The video games industry is a fitting example of what cultural innovations entail (Aoyama & Izushi, 2003). Beside filling the gap in literature, this research also aims at increasing performance of the Dutch Video games industry by exploring the relevant selection criteria. The following research question is investigated empirically:
How are game developers being selected by selectors in the video games industry?
Theory
This research uses existing literature to explore selection in the video games industry. However, experience goods are different from search goods (Nelson, 1970) and business to business selection is different from Business to consumer selection. Therefore, this research uses existing literature on Business to Business selection and related literature and tests whether it is applicable to an
environment where business developing experience goods are being selected by other businesses. This research uses selection criteria that were found to be important in a research done by Watt et al (2010). This theory is mixed with legitimacy theories described by Rao et al., 2008; Rao, 1994;
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Methodology
This research uses both qualitative research methods as well as quantitative research methods. Yin (2009, p. 132) termed this strategy a strong analytic strategy. Much attention has been paid to present reliable and valid results. First, this research extensively used findings in recent literature to formulate a relevant research question and to draw up hypotheses. All hypotheses cover different criteria and are formulated such that they were measurable. Second, the hypotheses were
investigated both quantitatively and qualitatively. The use of multiple research methods to collect the data (also referred to as data-triangulation) leads to increased credibility and validity. Third, the online questionnaire was designed such that both academic and practical relevance (pilot-testing the survey with industry experts) could be obtained. 19 game developers have responded to an online questionnaire and 3 selectors were interviewed.
Results
The research indicated that, contrary to expectations, pitching is not the most important selection method, 30% of the assignments are acquired by pitching. It was found that Intermediary
organizations play an important role in selection which is in concord with theory (McEvily and Zaheer, 1999; Saxenian, 1990). Also, follow-up assignments and self promotion was found to be important for getting assignments.
Past project performance and technical expertise are important selection criteria which is in concord with Watt et al (2010). Past project performance should be specified as past projects for the selector. Performance should be specified as the extent to which the game developers think along and
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Content
Abstract ... iv Acknowledgements ... v Executive summary ... vi Introduction ... vi Theory ... vi Methodology ... vii Results ... vii 1. Introduction ... 12. The video Games industry ... 3
2.1 Facts & figures ... 3
2.2 Previous research ... 3
2.3 Selectors & Gatekeepers ... 4
2.4 Video games ... 4
2.4.1 Applied video games ... 5
3. Selection ... 6
3.1 Experience goods vs. Search goods ... 6
3.2 B2B selection ... 6 3.3 Hypotheses ... 7 3.3.1 selection methods ... 7 3.3.2 selection criteria ... 8 4. Methodology ... 16 4.1 Sample selection ... 17
4.1.1 Sample selection: case studies. ... 17
4.1.2 Sample selection for online questionnaire. ... 18
4.2 Data gathering ... 18
4.2.1 Data gathering case studies ... 18
4.2.2 Data gathering online questionnaire ... 19
4.3 Data analysis... 21
4.3.1 Data analysis case studies ... 21
4.3.2 Data analysis online questionnaire ... 22
4.3.3 Cross-method analysis ... 23 4.4 Data reporting ... 23 4.5 Conclusion ... 24 5. Response ... 25 5.1 Qualitative research ... 25 5.2 Quantitative research ... 25
5.2.1 EDA-assumptions quantitative research ... 26
5.2.2 Data exploration ... 28
5.3 SPSS tests ... 28
6. Findings quantitative research ... 29
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6.2.8 Media legitimacy ... 35
6.2.9 Relations ... 37
6.2.10 Product focus ... 37
6.2.11 Innovativeness ... 38
7. Findings Qualitative research ... 39
7.1 Selection methods... 39 7.2 selection criteria ... 41 7.2.1 Price ... 41 7.2.2 External legitimacy ... 42 7.2.3 Market legitimacy ... 42 7.2.4 Scientific legitimacy ... 43 7.2.5 Historical legitimacy ... 43 7.2.6 Locational legitimacy ... 44 7.2.7 Certification legitimacy ... 44 7.2.8 Media legitimacy ... 45 7.2.9 Relations ... 46 7.2.10 Product focus ... 46 7.2.11 Innovativeness ... 47 8 Data triangulation ... 48 9. Conclusion ... 52
9.1 Answering the research question ... 52
9.1.1 What selection methods are used and how and why are they used? ... 52
9.1.2 What selection criteria are used and how and why are they used? ... 53
9.2 Contributions to literature ... 53
9.3 Managerial implications ... 55
10. Limitations and future research ... 57
References ... 59
Appendix A: online questionnaire research ... 65
Appendix B: Online questionnaire ... 70
Appendix C: Overview SPSS-tests ... 82
Appendix D: Case study protocol ... 85
Appendix E: SPSS output ... 89
Appendix F: Case study-database ... 115
Interview 1. ... 115
Interview 2 ... 118
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1. Introduction
Selection is of utmost importance to organizations. Especially the organizations being selected. The environment for making judgments about suppliers and their ability to deliver is complex, comprising high levels of ambiguity and uncertainty, competing stakeholder values and complicated
relationships as a result of multiple conflicting objectives (Watt et al, 2010). Given the complexities and underlying issues surrounding contractor selection, and the variety of criteria available, how then do clients choose suppliers? What criteria influence choice?
Most studies regarding selection theory focus on the last step of selection where consumers buy from suppliers (B2C: Business to Consumer). In this instance, the relevant selector is the
consumer. However, the products that consumers can choose from are already pre-selected and the suppliers of the consumers have chosen their own suppliers (B2B: Business to Business). Here the selector is thus a company. Despite its importance, the aspect of contractor selection remains largely unexplored, as evidenced by the very few studies reported (Watt et al., 2010). Although Watt et al filled the gap in literature by studying contractor selection criteria used in tenders, selection criteria for clients choosing contractors for experience goods are not yet studied despite the fact that pre-selection is especially important for experience goods (Hirsch, 1972). This study aims at filling this gap in literature.
Video games are a fitting example of experience goods, in which the value of the product can only be determined after consumption. Also, video games are a fitting example of what cultural innovations entail (Aoyama & Izushi, 2003). The cultural industries seem exceptionally suitable for studying the relationship and interaction between the selectors and the selected. This stems from the fact that within the cultural industries the role that the selectors play in the determination of value is generally more visible than in many other industries (Mol and Wijnberg, 2007). Also, the dilemmas experienced by managers in cultural industries are also to be found in a growing number of other industries where knowledge and creativity are key to sustaining competitive advantage
(Lampel et al., 2000).Therefore, this study focuses on the video games industry for exploring selection processes.
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where game developers are being contracted for developing a video game. Therefore, this study focuses on applied games as those games provide a fitting example of option (2) where game developers are contracted for making a video game.
The main purpose of this research is to explore how game developers are being selected for developing an applied video game. By exploring how game developers are being selected this research will develop a theory about B2B selection processes of companies involved in developing experience goods, thereby focusing on the applied video games industry for developing this theory.
The main research question being addressed in this study is:
How are game developers being selected by selectors in the video games industry?
The sub questions are:
1. What selection methods are used and how and why are they used? 2. What selection criteria are used and how and why are they used?
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2. The video Games industry
The previous chapter ended with the general research question of this study. This chapter provides the literature background information about the video games industry. Therefore chapter 2.1 discusses the facts and figures of the (Dutch) video games industry. Chapter 2.2 discusses previous research into the video games industry. Chapter 2.3 discusses the influence of selectors/gatekeepers in the Dutch Video games industry. Chapter 2.4 discusses definitions and classifications of video games.
2.1 Facts & figures
In this study the video gaming industry will be defined as all the actors involved in making video games. While most titles sold in the Netherlands come from the major international video game publishers, there is an active local video game industry with more than 100 companies in the Netherlands involved in developing and producing video games (Price Waterhouse Cooper (PWC), 2009). The video games market in the Netherlands rose by 21.1 percent in 2008, the third year in a row that growth exceeded 20 percent. The overall video games market will grow from € 585 million in 2008 to € 859 million in 2013 (PWC, 2009). The Benelux Game Initiative estimated even that 700 million is earned with making games in the Netherlands in 2007 (Janssen & Van der Meer, 2007, p. 73). The Netherlands is at the forefront of the industry in the development of serious games. These are games designed for educational purposes and provide interactive simulations that can be used in situations where real life training would be difficult or expensive (PWC, 2009).
2.2 Previous research
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(2006) for a description of how videogame design results from individuals creative actions focusing on companies in the U.S. However, there have not yet been any studies regarding the question, ‘How are game developers selected?’. This study aims at filling this gap in literature.
2.3 Selectors & Gatekeepers
The video games industry is part of the creative industry (Caves, p. 1) as well as the cultural industry (Aoyama & Izushi, 2003, Johns, 2006). One unique feature of creative industries is their use of intermediaries, who act not only as judges of talent and capability, but also as financiers and distributors (Caves, 2002). Hirsch (1972) terms these intermediaries ‘Gatekeepers’. Gatekeepers are also referred to as selectors (Wijnberg and Gemser, 2000; Wijnberg, 2004; Mol and Wijnberg, 2007). The selection system specifies the essential characteristics of the selected, consisting of actors that are competing with each other for recognition; and the selectors, consisting of actors whose decisions will influence the outcome of the process. The selection system therefore provides a shorthand description of the relation between the selectors and the selected. The selection system determines the value of an innovation (Wijnberg, 2004). Three basic types of selection systems are distinguished: market selection, peer selection, and expert selection (Wijnberg and Gemser, 2000). In the case of market selection, the producers are the selected and the consumers are the selectors. In peer selection, on the other hand, the selectors and the selected are part of the same group. In the case of expert selection, the selectors are neither producers nor consumers, but have the power to shape selection by virtue of specialized knowledge and distinctive abilities. Expert-selection is the selection system that will be studied in this research as game-developers are chosen by other companies to develop their games.
2.4 Video games
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2.4.1 Applied video games
Serious games
Zyda (2005) defines Serious games as a mental contest, played with a computer in accordance with specific rules, that uses entertainment to further government or corporate training, education, health, public policy, and strategic communication objectives. Serious games have more than just story, art, and software, they involve pedagogy: activities that educate or instruct, thereby imparting knowledge or skill. This addition makes games serious.
Funds for developing serious games are provided by organizations. For example companies, the government or foundations can use games for their purposes. Organizations can be considered the relevant selectors.
Advergames
Marketing departments and advertising agencies increasingly exploit the popularity of
video games by using in-game advertising opportunities or newly developed “adver” games (games with the goal to promote products) in their marketing campaigns. Advergames are games specifically designed to promote a product and are often played for free on the company’s Web site. Many different advertisers are experimenting with games to get their message across. Advertising games are in its infancy but is growing at double digit rates. Advertisers have entered the video game market as a means of reaching demographic groups, such as males 18-34, that are becoming more elusive as they watch less television than in the past and spend relatively more time playing games (PWC, 2009).
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3. Selection
Selection theory focuses on the relevant selection system for explaining performance differences (Wijnberg; 2004; Caves; Mol and Wijnberg, 2007). To compete successfully one’s products have to be valued and recognized as valuable. This is the starting point of looking at competitive processes from the perspective of the selection system. This study focuses on B2B selection for businesses involved in producing the experience good, applied video games.
This chapter is structured as follows. Chapter 3.1 distinguishes between search and experience goods in selection theory. Chapter 3.2 discusses B2B selection and in chapter 3.3
hypotheses are formulated. Chapter 3.3 is separated according to the research questions formulated in chapter 1.
3.1 Experience goods vs. Search goods
Nelson (1970) classifies products into search and experience goods according to consumers’ ability to obtain product quality information before purchase. Nelson argues that consumers conduct minimal pre-purchase information search for experience goods but perform extensive search for search goods. However some researchers have argued that internet enables consumers to learn from the experiences of others and to gather product information that is often difficult to obtain in offline settings therefore making all attributes searchable and erases differences between search and experience goods. However it is still argued that the type of information, the amount of information, the time spent processing each piece of information is different for search and experience goods (Johnson et al., 2003; Huang et al., 2009). Therefore, studies regarding selection theory for search good might not be applicable to situations in which experience goods are selected.
3.2 B2B selection
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studied well, this research uses the findings of different studies to test their suitability to a B2B selection environment of experience goods.
Contractor selection criteria used for tenders has been studied by Watt et al. (2010). Watt et al. found 3 criteria to be important selection criteria: tendered price, technical expertise and past project performance. However, it is unclear whether these criteria are also applicable to companies developing experience goods in general and companies developing applied video games in particular. Also, Watt et al. did not use legitimacy theories in their research. Legitimacy is a generalized
perception or assumption that the actions of an entity are desirable (Rao et al., 2008). For example; Watt et al. found reputation not to be an important selection criterion. However, legitimacy theories state that reputation is among others the outcome of past project performance. Also, studies done by Mol and Wijnberg (2007), WIjnberg and Gemser (2000) and Hirsch (1972) about cultural industries will be used to complement the selection criteria.
Thus, the selection criteria used by Watt et al. have some overlap as reputation is among others the outcome of past project performance. Therefore, in this research, legitimacy theories will be used as a starting point and will be complemented with other selection criteria used among others by Watt et al. (2010). In line with Choi and Kim (2008) who state that ‘generally’, supplier selection is a multi-criteria decision problem’, many hypotheses will be formulated by using different studies.
3.3 Hypotheses
As supplier selection is a multi-criteria decision problem (Choi and Kim, 2008) many hypotheses are formulated. Many hypotheses are drawn based on theory of selection processes regarding (B2B) selection of search goods as search goods are relatively much better studied compared to (B2B) selection of experience goods (see chapter 3.2).
3.3.1 selection methods
Pitches are widely used to select advertising agencies (Faisil and Khan, 2008). As it is unknown what advertising agencies have to offer to selectors, pitches are a way to make a more sophisticated judgement of the possible candidates. It is researched whether pitching is also used to select game developers.
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3.3.2 selection criteria
Price: Watt et al (2010) found that tendered price was an important selection criteria for evaluating
tenders. Therefore, in this research it is researched whether price is an important selection criterion for selecting applied game developers.
H2, H₀: Companies being cheaper compared to their competitors have equal success in being
selected.
H2, H₁: Companies being cheaper compared to their competitors have more success in being
selected.
It is expected that there is a negative relation between the price game developers offer and the amount of assignments the game developers process.
Because of the characteristics of experience goods, there are no product characteristics to evaluate the game developers (the quality of the product can only be determined afterward). Therefore, selectors need to rely on other information to select the game developers. A core element of the resource based perspective (Wernerfelt, 1984; Prahalad and Hamel, 1990; Barney, 1991) is the proposition that intangible resources such as reputation significantly contribute to performance differences among organizations because they are rare, socially complex, and difficult to trade and imitate (Barney, 1991; Peteraf, 1993). A reputation can help a firm contract with exchange partners through allowing the firm to lower costs, increase prices, and create competitive barriers
(Deephouse, 2000). However, Watt et al (2010) found that reputation was not an important selection criterion in selecting contractors for tenders. This research makes use of the definition of reputation proposed by Rao (1994). Rao states that reputation is a socially constructed entity and portrays reputation as the outcome of legitimization processes. Legitimacy is a generalized perception or assumption that the actions of an entity are desirable (Rao et al., 2008). Organizational theorists assert that legitimacy is an intangible asset that determines the ability of organizations to garner capital, personnel and customers, and thereby influences the survival of organizations (Rao, 1994 refering to Hannan and Freeman, 1989). Legitimacy is mainly about perception. Central to the
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locational legitimacy is distinguished. Rao (1994) added certification legitimacy to these 5
dimensions. Other researchers added media legitimacy (Sheafer, 2001; Aerts and Cormier, 2009).
External legitimacy: a seemingly easy way for new ventures to gain legitimacy is through a formal
alliance with an established entity (Gans and Stern 2003; Rao et al., 2008), this is termed external legitimacy by Rao et al. Rao et al (2008) states that an alliance with a successful partner helps a new venture overcome stakeholder uncertainty about its capabilities and its inexperience in launching similar products. As applied video games are a relatively new phenomena with no established and well-known companies it is researched whether alliances in general influence selection.
H3, H₀: :Companies forming alliances with other game developers have equal success in being
selected compared to companies not forming alliances.
H3, H₁: Companies forming alliances with other game developers have more success in being selected
compared to companies not forming alliances.
It is believed that there is a positive relation between game developers that have allianced with other game developers and the chance of being selected as alliances might overcome selectors uncertainty about its capabilities and its inexperience.
Market legitimacy: A way for new ventures to acquire legitimacy is by hiring executives with
marketing and management experience in established, related fields. This is called market legitimacy by Rao et al. (2008). The presence of experienced professionals from related fields suggests that the new venture understands customers well and that the firm is market oriented. Also, it will provide new ventures with important capabilities and experiences which improves stakeholder perceptions of the likely success of the firm (Rao et al., 2008). It is also believed by this author that hiring experienced professionals from the same field can increase legitimacy in the eyes of the relevant stakeholders. Thus it is studied whether experienced employees influence the success in being selected.
H4, H₀: Companies with more experienced employees have equal success in being selected
compared to companies with less experienced employees.
H4, H₁: Companies with more experienced employees have more success in being selected compared
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As experienced employees might improve selectors perceptions of the likely success of the firm it is believed that there is a positive relation between companies with more experienced employees and the chance of being selected.
Scientific legitimacy: New ventures in emerging industries must convey to stakeholders that they
understand and can work with the latest scientific ideas in the field. This is called scientific legitimacy by Rao et al. (2008). In this research it is tested whether assigning academics from well respected studies can increase selection. The presence of academics from well respected studies will signal to stakeholders that the new venture understands and can work with the latest trends in the field. Deeds et al. (2004) also indicated that this ‘halo effect’ can create legitimacy. Therefore, it is studied that game developers having employees from universities and art schools have more success in being selected.
H5, H₀: Companies with employees from Art schools and universities have equal success in being
selected compared to companies with employees from other studies.
H5, H₁: Companies with employees from Art schools and universities have more success in being
selected compared to companies with employees from other studies.
As assigning academics from well respected studies can convey to selectors that they understand and can work with the latest scientific ideas in the field, it is expected that there is a positive relation between companies with more academics from well respected studies and the chance of being selected.
Historical legitimacy: Perhaps the most convincing way a new venture can gain legitimacy is by
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expertise is thus termed historic legitimacy in this research. It is studied whether companies with a history of successful products (advergames/serious games) have more success in being selected compared to companies with no such history.
H6, H₀: Companies with a long history of making applied video games have equal success in being
selected compared to companies with no such history.
H6, H₁: Companies with a long history of making applied video games have more success in being
selected compared to companies with no such history.
As a history of making applied video games can provide selectors with information about experience and thus expertise, it is expected that companies with a long history of making applied video games have a higher chance of being selected for making applied video games.
Locational legitimacy: Research on clusters suggest that new ventures in emerging industries can
gain legitimacy by locating themselves in areas with large number of related firms (Pouder and St. John, 1996; Pe’er et al., 2008). This is called locational legitimacy by Rao et al. (2008). Localization externalities can be categorized into production enhancements and heightened demand. Demand enhancement results from lower consumer search costs and risk: consumers prefer to patronize a location where they can inspect multiple goods or access a second-best option if necessary (Kalnins and Chung, 2004). Production enhancements include: labor market pooling; advantages of backward and forward linkages associated with large local markets; shared infrastructure available to co-located firms; technological and knowledge spillovers; information externalities about demand or the feasibility of production at a particular location; and lower exit barriers, which may, in turn, lower entry costs. Some entrants may be able to appropriate resource spillovers if they locate in resource rich environments (Pe’er et al., 2008). Therefore, the presence of related firms can help new ventures in these clusters gain legitimacy. Therefore it is studied whether companies locating near other game developers have more success in being selected compared to companies not choosing such location.
H7, H₀: Companies locating near other game developers have equal success in being selected
compared to companies not choosing such location.
H7, H₁: Companies locating near other game developers have more success in being selected
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As a location near other game developers can enhance production and heighten demand, it is expected that there is a positive relation between the amount of competitors at the location of the game developer and the chance of being selected.
However, convenience in the form of a location of the game developer near the selector might also be an important criterion for selectors. It is unclear whether location is an important selection criterion in selecting companies. Location was considered to be of average importance as a selection criterion in a study of Dickson (1966). Therefore it is studied whether companies are mainly selected by selectors in the same region.
H8, H₀: Selectors select companies located in the same region as the selector. H8, H₁: Selectors select companies located in other regions as the selector.
It is expected that game developers are mainly selected by selectors in the neighborhood of the game developers.
Certification legitimacy: Certification contests are social tests of products and organizations.
Victories in certification contests legitimate organizations and validate their reputation. This is called certification legitimacy by Rao (1994). According to Rao, contests structure search in crowded and confused markets and circumvent the issue of measuring capabilities. Also, the legitimation provided by certification contests consists of small chance events that trigger a self-reinforcing reputation and generate increasing returns to organizations. This is consistent with the Matthew effect described by Merton in 1968 (Rao, 1994). The Matthew effect simply means that higher status actors derive greater rewards than lower-status actors for performing an identical task. Watt et al. (2010) in their study about evaluation criteria for selecting contractors in a tender found that past project
performance was considered an important selection criterion. However, information regarding past project performance of game developers is difficult to obtain (in contrast to tenders) and the value of the product is difficult to assess even after consumption. Therefore, it is believed that selectors look for other information to assess past project performance. It is believed that selectors will look for game developers that have won awards. Thus awards are an indication of past project performance. It is studied whether companies having won certification contests have more success in being selected compared to companies that have not won certification contests.
H9, H₀: Companies having won certification contests have equal success in being selected compared
13 H9, H₁: Companies having won certification contests have more success in being selected compared
to companies that have not won certification contests.
As certification contests validate reputation and structure search, it is believed that having won certification contests can increase the chance of being selected. It is believed that selectors look for game developers that have won certification contests as other information about the reputation of the game developer is very difficult to obtain.
Media legitimacy: As institutional intermediaries specializing in disseminating information about
organizations or in evaluating their outputs, public media play an important role in legitimating processes (Rao, 1998). Media coverage of certain issues raises the salience of issues in the public’s agenda and is a reasonable indicator of the public’s knowledge and opinions about firms within a few months of the publication date (Deephouse, 2000). Media research shows that the agenda-setting effect is especially strong for unobtrusive issues or issues with which individuals have little personal contact (Aerts and Cormier, 2009). Also, the diffusion of particular fads and fashions is either blocked or facilitated by mass media and serve as “institutional regulators of innovation”. Styles afforded coverage are imitated and reproduced on a large scale until the fad has run its course (Meyersohn and Katz, 1957). The media is an institution that reduces stakeholders uncertainty about a firm’s characteristics, filling reputation’s signaling role (Weigelt and Camerer, 1988). Because media attention of national media increases the awareness of a firm’s reputation it is studied whether national media attention increases the success of being selected.
H10, H₀: Companies that were covered by national media attention have equal success in being
selected compared to companies that were not covered by national media attention.
H10, H₁: Companies that were covered by national media attention have more success in being
selected compared to companies that were not covered by national media attention.
As media attention is a reasonable indicator of the knowledge and opinions of a game developer and it reduces selectors uncertainty about a firm’s characteristics, it is believed that game developers that were covered by media attention increases the chance of being selected.
Relations: Firms are also tempted to influence selectors’ judgment in other ways. If a firm is able to
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as organizational capital resources (Barney, 1991). Empirical studies find few partnerships formed without prior direct or indirect ties (Li and Rowley, 2002). Therefore, it is studied whether companies that are acquainted with selectors have more success in being selected compared to companies that are not yet acquainted with the selectors.
H11, H₀: Companies that are acquainted with selectors have equal success in being selected
compared to companies that are not yet acquainted with the selectors.
H11, H₁: Companies that are acquainted with selectors have more success in being selected
compared to companies that are not yet acquainted with the selectors.
As it has been found that few partnerships are formed without prior direct or indirect ties it is expected that game developers that already know the selectors have more success in being selected compared to game developers that do not already know the selectors.
Product focus: Porter was the first who distinguished focus/niche as a business strategy. Focus is
based on adopting a narrow competitive scope within the industry. By focusing on one specific product, companies can become specialists and obtain specialized knowledge. Watt et al (2010) described technical expertise as important selection criterion for selecting contractors for tenders. As technical expertise is gained by experience (see historical legitimacy), it is believed that a focus on applied games can increase the chance of being selected as product focus will signal to selectors that the game developer has expertise in the specific product. It is believed that companies focusing on applied games only have more success in being selected compared to companies with no such focus. Therefore it is studied whether a focus on applied games increases the success of being selected.
H12, H₀: Companies focusing only on applied games have equal success in being selected compared
to companies not focusing on applied games.
H12, H₁: Companies focusing only on applied games have more success in being selected compared
to companies not focusing on applied games.
It is expected that game developers focusing on applied games only have more success in being selected as selectors look for game developers with specific expertise.
Innovativeness: In many forms of cultural industries, recognition and attribution of value is strongly
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differentiation as an important business strategy for creating value. Innovation as differentiation strategy is a way of creating value and according to many authors, starting with Schumpeter, the most important way (Wijnberg, 2004). Wijnberg and Gemser (2000) state that innovation is one of the means to gain market recognition for cultural products. In the visual arts, however, innovation had been largely limited to variations based on existing styles and themes. More radical forms of artistic innovation that break with existing standards had rarely been used as a deliberate strategy. This is not any different from any industry as most innovations are incremental in nature(Abernathy and Utterback, 1978; Anderson and Tushman, 1990). Also, researchers found that people perform very poorly at selecting creative ideas (Faure, 2004; Rietzschel et al.,2006). However, as
overproduction is one of the characteristics of cultural industries (Hirsch, 1972) it is believed that innovative products have more chance of being selected because it is a way to stand out in the selection process.
H13, H₀: Companies being more innovative compared to their competitors have equal success in
being selected compared to companies being less innovative.
H13, H₁: Companies being more innovative compared to their competitors have more success in
being selected compared to companies being less innovative.
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4. Methodology
As became apparent in the previous chapters, not much is known regarding B2B selection of
experience goods in general and B2B selection of video game developers in particular. An exploratory research is undertaken as there is not much known about the situation and as the goal of this
research is to gain a deeper understanding of the issue under study. Exploratory research is
characterized by its flexibility, for an exploratory study, any research method can be used. Also, the various methods that can be used are not mutually exclusive (Yin, 2009, p. 9 & 13). Survey methods are advantageous when the research goal is to describe the incidence or prevalence of a
phenomenon (Yin, p. 9). Case studies are preferred for answering “how” and “why” questions (Yin, p. 2). Therefore qualitative research and quantitative research will be used both to complement and to converge data in this research. Yin (2009, p. 132) termed this strategy a strong analytic strategy. The hypotheses formulated in chapter 3.3 are used for the quantitative research but also to structure the qualitative data analysis. Qualitative research permits to investigate certain issues further. Thus, this mixed methods research permit to address more complicated research questions and collect a richer and stronger array of evidence than can be accomplished by any single method alone (Yin, p. 63).
Research question Game developers Selectors
How are game developers being selected by selectors in the video games industry?
1. What selection methods are used and how and why are they used?
2. What selection criteria are used and how and why are they used?
Questionnaire Questionnaire Questionnaire Case study Case study Case study
Chronologically, this study includes the following steps. First, literature about selection criteria was reviewed (See chapter 3). The goal of this literature review was to asses possible selection criteria. Second, an online questionnaire was developed for game developers and analyzed in SPSS. Then, cases were studied where interviews with selectors were the primary source of evidence and data was analyzed. Finally, cross-method analyses were performed. This method of validating
This chapter is structured as follows.
research are selected. Also, this chapter discusses how cases are selected. Chapter 4.2 discusses how data will be gathered for the quantitative research as well as the qualitative research. Chapter discusses how data will be analyzed. Chapter 4.4 discusses how data will be presented and Ch 4.5 concludes with reliability and validity aspects of the research.
4.1 Sample selection
4.1.1 Sample selection: case studies
Case studies are in depth studies of particular cases. The cases in this research are found by using the internet. The cases concern situations in which a particular game developers (or developers) have been selected for developing an applied video game.
usually be satisfied by multiple cases (Yin, p. 53). Each case must be carefully selected so that it either (a) predicts similar results (literal replication) or (b) predicts contrasting results but for anticipatable reasons (theoretical replication). Literal replication is used in this research. However, predicting similar results in the selected cases is difficult as there have not yet been studies regarding selection of game developers. However in this research it is assumed that s
selection methods for selecting advergame developers or serious game developers do not differ. This assumption will be tested in the current research. For the number of literal replications, an
appropriate analogy from statistics is t
desired to detect an “effect”. Designating the number of replications depends upon the certainty a researcher wants to have about the multiple
number of cases) (Yin, p. 58). However,
supplement the findings found by the quantitative research. Certainty is thus obtained by data triangulation, as will be described in the forthcomin
in concord with Yin (p. 56-58) the case study protocol was flexible such that when important
discoveries occurred during the conduct of one of the individual case studies, alternative cases could be selected or changes in the data collection process could be handled.
Quantitative method Conducting online survey Qualitative method
This chapter is structured as follows. Chapter 4.1 discusses how the sample of the quantitative research are selected. Also, this chapter discusses how cases are selected. Chapter 4.2 discusses how data will be gathered for the quantitative research as well as the qualitative research. Chapter discusses how data will be analyzed. Chapter 4.4 discusses how data will be presented and Ch 4.5 concludes with reliability and validity aspects of the research.
: case studies.
epth studies of particular cases. The cases in this research are found by using the The cases concern situations in which a particular game developers (or developers) have been selected for developing an applied video game. The rationale for single-case designs cannot usually be satisfied by multiple cases (Yin, p. 53). Each case must be carefully selected so that it either (a) predicts similar results (literal replication) or (b) predicts contrasting results but for
ical replication). Literal replication is used in this research. However, predicting similar results in the selected cases is difficult as there have not yet been studies regarding selection of game developers. However in this research it is assumed that selection criteria and selection methods for selecting advergame developers or serious game developers do not differ. This assumption will be tested in the current research. For the number of literal replications, an
appropriate analogy from statistics is the selection of the criterion for establishing the sample size desired to detect an “effect”. Designating the number of replications depends upon the certainty a researcher wants to have about the multiple-case results (the greater certainty lies with the
number of cases) (Yin, p. 58). However, in this research the case studies are used to complement and supplement the findings found by the quantitative research. Certainty is thus obtained by data triangulation, as will be described in the forthcoming chapters. Three cases were selected. However,
58) the case study protocol was flexible such that when important
discoveries occurred during the conduct of one of the individual case studies, alternative cases could or changes in the data collection process could be handled.
Conducting Analyzing Data Conducting case studies Analyzing Data 17
Chapter 4.1 discusses how the sample of the quantitative research are selected. Also, this chapter discusses how cases are selected. Chapter 4.2 discusses how data will be gathered for the quantitative research as well as the qualitative research. Chapter 4.3 discusses how data will be analyzed. Chapter 4.4 discusses how data will be presented and Chapter
epth studies of particular cases. The cases in this research are found by using the The cases concern situations in which a particular game developers (or developers) have
case designs cannot usually be satisfied by multiple cases (Yin, p. 53). Each case must be carefully selected so that it either (a) predicts similar results (literal replication) or (b) predicts contrasting results but for
ical replication). Literal replication is used in this research. However, predicting similar results in the selected cases is difficult as there have not yet been studies regarding
election criteria and selection methods for selecting advergame developers or serious game developers do not differ. This assumption will be tested in the current research. For the number of literal replications, an
he selection of the criterion for establishing the sample size desired to detect an “effect”. Designating the number of replications depends upon the certainty a
case results (the greater certainty lies with the larger in this research the case studies are used to complement and supplement the findings found by the quantitative research. Certainty is thus obtained by
data-hree cases were selected. However, 58) the case study protocol was flexible such that when important
discoveries occurred during the conduct of one of the individual case studies, alternative cases could
18 Interview date Function of respondent Type of game developed
7 June Internet marketer of a
insurance company
Advergame
2 June Public guidance and education
of a museum
Serious Game
21 June Account manager of advertising
agency
Intermediary organization for Advergames
4.1.2 Sample selection for online questionnaire.
The sampling frame consisted of all the applied video game developers in the Netherlands. The sampling frame for the online questionnaire was constructed by using the internet. First,
www.gamesindustrie.nl was used to select game developers. www.gamesindustrie.nl is a website where game developers can be found. Second, Google was used to supplement the list. In the final stage gaming groups on LinkedIn (social media) were checked to complete the list. The websites of the game developers were used to check whether the game developers were active making advergames, serious games and/or interactive games. In total, 62 game developers were found, developing advergames or serious games. The website gamesindustrie.nl distinguishes 52 serious game developers and 29 advergame developers. The game developers offering standardized solutions were excluded from this study as this study focuses on non-standardized products which cannot be tested beforehand (experience products). 22 game developers were according to their website active with making advergames, 30 were active making serious games. The other game developers were active making both advergames and serious games.
4.2 Data gathering
4.2.1 Data gathering case studies
19
with the interviews with the relevant selectors. To assure reliability a case study protocol is used (Appendix D ). The case study protocol is essential when doing a multiple-case study (Yin, p. 79). Also, the same methods of gathering (and analyzing) information will be used. Only with such replication would the original findings be considered robust (Yin, p. 54). Also, tactics will be used to alleviate possible interviewer and informant biases (Bourgeois and Eisenhardt 1988). First, the interviews with the key informants of the Video Gaming Industry are tape-recorded. This tactic will enable the direct access to the original discussion and pay attention to any part of it at later stages. Also, in concord with Yin (2009, p.106), the interviews will be guided conversations rather than structured queries; the actual stream of questions will be fluid rather than rigid. However, a consistent line of inquiry will be pursued.
4.2.2 Data gathering online questionnaire
In concord with Yin (2009, p. 8), quantitative research will be used to answer ‘what’ questions: “What selection method is used?” and “What selection criteria are used?” The question “what selection method is used?” Is actually a form of “how many” line of inquiry. This type of questions are more likely to favor survey methods. Survey methods are advantageous when the research goal is to describe the incidence or prevalence of a phenomenon (Yin, p. 9). The method that is used is an online questionnaire1. Web based surveys have several advantages above other types of methodologies. The advantages are: reduction of time and cost, provide readily usable data,
soliciting responses for online surveys is easy, directly seeing responses, the use of email addresses is likely to infringe less on the privacy of the respondent, improved data quality, possibility to use interaction mechanisms, absence of interviewer bias and convenience for respondents (Singh et al., 2009; Ekman et al., 2007; Van Selm and Jankowski, 2006; Cooper and Schindler; Fricker and
Schonlau, 2002).
For assuring good response rates, the questionnaire used is designed according to the criteria in Appendix A: the questions are simple, relevant by using session keys and an explanation, multiple item screens are used, text box entries are used and a logical pattern is followed. Also, most
questions are designed such that interval data is created. Interval data can be used for parametric tests which are generally considered more powerful compared to non-parametric tests (Blair and Higgins, 1980; 1985 in Rasmussen and Dunlap, 1991). The questionnaire was discussed with another researcher and an industry expert, such that definitions and questions could be fine-tuned.
Furthermore, before the questionnaire was put online, the survey was pilot-tested with an industry expert, ensuring that definitions and questions are understandable and relevant for the industry. An
1
20
e-mail with the link to the questionnaire was sent to CEO’s or managers of the companies. Using E-mail as a solicitation method has the advantage of being quick and easy. The disadvantage is that spam filters may block the e-mail (Van selm and Jankowski, 2006). The e-mail is constructed according to the criteria in appendix A: an incentive is used to trigger participation, confidentially is confirmed, the purpose is clearly stated, appropriate contact information is provided, information about the cost (time) is provided, a direct link to the questionnaire is provided and the e-mail is simplified. To reduce non-response a follow-up mailing will be sent to the game developers that have not yet completed the questionnaire after one week. Also, to alleviate possible non-item response on important questions, some questions are necessary to answer in order to continue with the
questionnaire. The standard reliability percentage is mostly set at 5% which means that the reliability of the hypothesis is 95%.
The goal of the online questionnaire is to answer the question, how are game developers selected? This question is separated in two sub questions: ‘What selection methods are used?’(see table 4.1) and ‘What selection criteria are used?’ (see table 4.2). The questions of the questionnaire are designed to answer these research questions. To answer those questions, explaining variables are needed. The explaining variables are covered by question 31 which asks for the average amount of assignments processed each year. This question is designed to get interval data.
What selection methods are used? Hypotheses
(Chapter 3.3)
Questions (Appendix B)
Data Type Related literature
H1 38, 39 Ordinal, nominal Faisil and Khan, 2008
Table 4.1
What selection criteria are used? Hypotheses
(Chapter 3.3)
Questions (Appendix B)
Data type Related literature
H2 16, 17, 18 Interval Watt et al., 2010
H3 9 Nominal Gans and Stern 2003; Rao et al., 2008
H4 24 Interval, ordinal Rao et al., 2008
H5 25, 26 Ordinal Rao et al, 2008; Deeds et al., 2004; Watt et
al., 2010
H6 1, 33 Interval Rao et al., 2008; Rao, 1994; Hannan and
Freeman, 1984; Garvin, 1993; Watt et al., 2010
H7 10, 12 Nominal, Interval Rao et al., 2008; Pouder and St. John, 1996; Pe’er et al., 2008; Kalnins and Chung, 2004
H8 11 Nominal Dickson, 1966
H9 5, 6 Nominal Rao, 1994; Watt et al., 2010
H10 7, 8 Nominal Rao, 1998; Deephouse, 2000; Aerts and
21
H11 40, 48 Nominal Mol and Wijnberg, 2007; Barney, 1991; Li
and Rowley, 2002
H12 20 Nominal, interval Watt et al., 2010
H13 41 Nominal Hirsch, 1972; Wijnberg and Gemser, 2000;
Wijnberg, 2004; Abernathy and Utterback, 1978; Anderson and Tushman, 1990; Faure, 2004; Rietzschel et al.,2006
Table 4.2
4.3 Data analysis
The central tenet of exploratory research is that data should be explored. In exploratory data analysis the researcher has the flexibility to respond to the patterns revealed in the preliminary analysis of the data. During the process of exploratory data analysis, a careful statistician always goes back and forth to add variables to or take variables out of the model. Exploratory data analysis, which aims at suggesting a pattern for further inquiry, contributes to the conceptual or qualitative understanding of a phenomenon. Although it deals with numbers, the ending point is not statistical figures. Rather the product is the hypothetical insight of the essential feature or pattern of an event. In other words, the major concern is not "how much," but "what" and "how" (Yu, 1994). Thus patterns in the collected data guide the data analysis or suggest revisions to the preliminary data analysis plan. The flexibility is an important attribute of this approach (Cooper and Schindler, 2006, p. 472).
Exploratory Data Analysis (EDA) is not simply a set of techniques but an attitude towards the data (Tukay, 1977 in Behrens, 1997). In EDA the researcher entertains numerous hypotheses, looks for patterns, and suggests hypotheses based on the data, with or without theoretical grounding. While keeping an eye on the original hypotheses, working in an exploratory mode allows broader questions such as: how are the independent variables related to each other and the dependent variable? Also, the researchers must have a willingness to use any technique that helps ensure a rich mental model of the data that fits closely with the true form of the data (Behrens, 1997). In this research, the qualitative research and quantitative research were first analyzed separately. Followed by cross-method analysis.
4.3.1 Data analysis case studies
22
One of the most desirable techniques for case study analysis is to use pattern matching logic. This logic compares an empirically based pattern with a predicted one (or with several alternative predictions). If the patterns coincide, the results can help a case study to strengthen its internal validity. This strategy help to focus attention on certain data and to ignore other data. This strategy also help to organize the entire case study. In this research pattern matching logic will be used by comparing the patterns found in the case studies with the patterns found in the quantitative research.
4.3.2 Data analysis online questionnaire
The data obtained by the online questionnaire will be analyzed in SPSS. For an overview of the data-analysis methods, please see Appendix C for a description. The first step in the data-analysis will be to analyze the interval data for parametric assumptions. Parametric analysis of data is considered a better strategy than non-parametric analysis because the former appears to be more powerful than the latter (Rasmussen & Dunlap, 1991). Parametric tests are preferable to non-parametric tests, as long as the sample-size is not very small, they provide approximately 5% more power than rank tests (Peat and Barton, 2005, p. 25). The second step in the analysis will be to analyze whether interval data which cannot meat parametric assumption can be re-expressed such that parametric tests can be used (see appendix C). Correlation tests will be used to test whether two aspect of the gathered data are related. The Spearman’s Rho test will be used when data is non-normal and the normal correlation test will be used when data is found to be normal. To compare two independent groups when data is found to be normal, the T-test will be used. When data is found to be non-normal, the non-parametric alternative for the T-test is used: The Mann-Whitney test.
Skewness, kortosis and outliers can all distort a normal distribution. If a variable has a skewed distribution, it is sometimes possible to transform the variable to normality using a
mathematical algorithm so that the outliers in the tail do not bias the summary statistics and P values (Peat and Barton, 2005, p. 25). If the sample size is small (less than 30), then the variable would have to be perfectly normally distributed rather than approximately normally distributed before
parametric tests could be used (p. 43). If it is not possible to re-express the data, non-parametric tests will be used (see Appendix C). The second step is to test for outliers. For each hypothesis, tests will be used to identify possible outliers. Outlier tests tell you, on the basis of some simple
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4.3.3 Cross-method analysis
In this research there is one dependent variable: selection. If for this outcome, the predicted value has been found, and at the same time alternative patterns of predicted values have not been found, strong causal inferences can be made (Yin, 2009, p. 136-137). Also, when the same pattern is found in the other cases (cross-case analysis (Yin, 2009, p. 156-160)), even stronger conclusions can be drawn. The inferences can be even stronger when the same pattern is found in the survey data as well. By using this technique all reasonable threats to validity will be identified. This technique can be described as Data triangulation. The data from the three cases will be compared with each other and with the data from the survey. Data triangulation is the collection of information from multiple sources but aimed at corroborating the same fact or phenomenon such that facts or events have been supported by more than a single source of evidence. With data triangulation, the potential problems of construct validity also can be addressed because the multiple sources of evidence essentially provide multiple measures of the same phenomenon (Yin, p. 117).
4.4 Data reporting
In this research a case study database is maintained (Appendix F) as well as a quantitative database (Appendix E). Also, it is possible to follow the derivation of evidence from initial research questions to ultimate conclusions. It is possible to trace each step in either direction (from conclusions back to initial research questions or from questions to conclusion). The process is tight such that evidence presented is assured the same evidence that was collected during the data collection process. The study results are validated by comparing cases with each other and comparing it with the survey results (and vice versa). The information obtained through the interviews will be checked against data found in secondary sources whenever possible. This use of multiple data sources will reinforce belief in the validity of the findings (Eisenhardt 1989; Yin 2009).
24
reported in the nest chapter. Fourth, the findings of the quantitative data, the qualitative data and the literature research will be combined and will be presented in the next chapter.
4.5 Conclusion
25
5. Response
This chapter discusses general research findings concerning the response and non-response and what it means for the research. Chapter 5.1 gives a short introduction into the cases studied for the qualitative research. Chapter 5.2 discusses the response and non-response of the quantitative research. Data will be explored according to Exploratory Data Analysis methods. Also, this chapter discusses what implications the response has for data analysis. Chapter 5.3 discusses the tests that will be used in the quantitative research.
5.1 Qualitative research
Table 4.3 lists the selectors included in this study, together with their industry and the time of having conducted the interview. The selectors names are not mentioned by agreement with the
participants. 3 case studies were performed:
Case 1: This study explored the selection of a game developer, selected for a highly successful
advergame on the social network Hyves.
Case 2: This study explored the selection of a game developer, selected for a serious game at a
government organization.
Case 3: This study explored the selection of game developers at an intermediary organization for
various advergames.
5.2 Quantitative research
26
Reasons for this could be that not all questions are applicable to all companies or that some companies did not want to answer some particular questions because of confidentiality matters.
5.2.1 EDA-assumptions quantitative research
The dependent variable is the average amount of assignments processed each year. With the Shapiro-Wilk test it can be tested whether data is normally distributed (Appendix C). The mean amount of assignments is 8, with a minimum of 1 and a maximum of 25. The Shapiro-Wilk test has a significance level of ≤0,05, namely 0,002 which means that the hypothesis that the variable, ‘average amount of assignments’ is normally distributed is rejected, the data is non-normally distributed. Re-expressing the data is a possibility to normalize the data. However, re-Re-expressing the data in the current situation does not make the data normal as the sample is relatively small. If the sample size is small (less than 30) then the variable would have to be perfectly normally distributed rather than approximately (Peat and Barton, 2005, p. 43). However, it appeared that the data is not normally distributed as indicated above. Therefore, non-parametric test will be used.
In this research outliers will be analyzed and removed in concord with EDA (Behrens, 1997). The dependent variable is the average amount of assignments processed each year. This variable is very important in testing the criteria which are important for selection, therefore this variable is tested for outliers. The box plot is a graphical representation of data that shows a data set’s lowest value, highest value, median value, and the size of the first and third quartile. The box plot is useful in analyzing small data sets.
27 Outlier research: quantitative
As indicated in the section above, case 14 is described as an outlier. However, case 14 is not excluded from this research as described above. Case 14 processes on average 25 assignments a year (sample mean is 8, sample median is 4) . The game developer exists 11 year (sample mean is 8, sample median is 6). The game developer consists of 24 people (sample mean is 12, sample median is 9). The focus on making applied video games and they have won 7 awards (sample mean is 1, sample
median is 0). They received national, regional as well as local media attention from television, radio, newspapers and trade journals. They work together with other game developers and are settled in south-Holland and they get assignments mainly from the industry, education and business services from all over the Netherlands. They focus on serious games and advergames and the budget for developing an advergame is on average 50.000 while the budget for developing a serious game is 125.000 on average. Experience and education is important for them to select new employees. Employees are on average 6 years active in the company (sample mean is 4,9, sample median is 5). 40% of the employees did art school (sample median is 30%) 10% did university (sample median is 10%). The game developer stimulates extra training. In their history they have processed about 250 game assignments (sample mean is 46, sample median is 15). The game developers has participated in about 50 pitches (sample mean is 15, sample median is 10) and receives about 10 pitch proposals in one year (sample mean is 6, sample median is 5) of the 10 proposals, they refuse 5 (50%) (sample median is 33%). The game developer wins on average all the pitches in which they participate (sample median is 75%). 20% of the assignments of the game developer are acquired by pitching (sample median is 30%). Like 53% of the respondents, the game developer has a team specialized in pitching. For most assignments they receive, one of the employees already knew the selector. Also, like most of the game developers, they think that they are being found by means of their network. The game developer thinks they pitch on average more innovative concepts and they comply strictly with the requirements in the pitch proposal. The game developers does not pitch cheaper prices compared with their competitors on average.
Outlier research: qualitative
1 selector, who had selected this game developer is interviewed by telephone to get more
information about case 14. The selector is active in the educational branch. In 2001 the selector got to know the respondent. The selector had some assignments for a game developer, including a game and websites with mini-games. 3 game developers were selected to pitch their ideas. The three game developers were selected because their competences did fit with the assignments as in 2001,
28
based on the criteria innovativeness and price. After the assignment was completed, the game received many positive reviews and responses and won several certification contests. The selector was very pleased with the result and consequently asked the respondent to complete more
assignments. Meanwhile the selector spoke with more game developers at festivals and conferences and was reinforced in the belief that the respondent was the best game developer possible for their assignments.
5.2.2 Data exploration
It is also tested whether there is a difference in the average amount of assignments processed between game developers that develop advergames and game developers that develop serious games. There is one game developer, according to the website active with developing both
advergames and serious games (case 14: see outlier research). This case is excluded. It appears that game developers that develop advergames (sig= 0,05) process on average more assignments in a year compared to game developers developing serious games.
Thus game developers that develop advergames process on average more assignments in a year compared to game developers developing serious games. Therefore, in this research all hypotheses will be analyzed first for all game developers, second for game developers developing advergames and third for game developers developing serious games. It was possible to indicate 6 advergame developers and 8 serious game developers. 5 game developers did not answer this question.
