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The next task is to analyse the connections between the innovation patterns among different classes of innovations, and this gives us the following research question:

Q1b. What kinds of interconnections are there between the patterns of different kinds of innovations?

Interconnections between innovative activity in hardware and software will shed light on the dynamics of complementary industries. The interconnections between technological and stylistic innovations within software will offer insight into the specificities of innovations within cultural and creative industries. This follows the call by Cappetta et al. (2006, p. 1286) to explore the complementarities between stylistic and technological innovations.

Furthermore, the patterns observed need to be explained through the micromechanisms that produce them. The interest here is on entries as well as on the procedures followed in the creation of new games. The innovation process is not seen as random but as a purposeful process directed by factors both internal and external to the firm. This results in the following research question:

Q1c. What factors direct the innovation process?

During the interviews it became apparent that the development firms actively communicate with each other. The next question thus aims at explaining this phenomenon.

Q1d. What factors motivate communication among firms?

The rest of the questions relate to the competitive process. The literature on cultural and creative industries highlights the non-utilitarian nature and the horizontal differentiation of the products. In addition, a specific characteristic of the cultural and creative industries is the plurality of gatekeepers whose scrutiny the products must pass to reach the consumer. Moreover, the consumers know which cultural products they like only after consumption and their preferences change through cumulative taste formation. All these characteristics imply that within the cultural and creative domain performance criteria are fuzzy and remain so independent of market age. This questions the accuracy of the assumption of the industry life-cycle theory of transition from vague to specific and well-defined performance criteria.

Furthermore, the economies of scale and cumulative learning that give rise to incumbent advantage appear not to be as strong in the cultural and creative domain as the industry life-cycle theory posits.

The reproduction of creative content, i.e. manufacturing CDs, DVDs, books etc., seems mature, with large scales and low unit costs. However, the value of the product is manufactured in the creative process in which economies of scale and cumulative learning are less. Whether it is more efficient to develop several games at a time in the same studio or just one or a small number of games in each studio is not known. Furthermore, the extent to which game developers become more efficient through cumulative learning is perhaps not equal to the assumptions of the industry-life cycle theory as each product needs to be different from the previous ones. The work on cultural and creative industries implies that management challenges grow disproportionately to firm size.

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Furthermore, Baumol‘s cost disease may prohibit the development of economies of scale in cultural and creative production. This means that efficiency gains and scale economies in creative work are debatable. In addition, dominant artists can charge a premium compared to lesser known variants, which goes against the assumption of cost reduction following the emergence of the dominant design.

To understand the competitive process in the games industry, concentration, entry and exit rates as well as firm numbers need to be analysed. Due to restrictions on data the industry concentration can be calculated only for the past two years and data on the entry and exit rates in the software side of the games industry can be collected only concerning Finnish firms. Statistics on the Finnish case are not representative of the global games industry but can indicate changes in the ability of the global market to absorb products from entering firms. This translates into the following questions:

Q2a. What is the level of concentration in the games industry?

Q2b. How has the ability of the game market to absorb new entrants changed in 1990-2007?

After diagnosing the competitive process, the micromechanisms that produce competition are explored. The first task is to find out how the executives of the firms perceive competition. This gives us the following research question:

Q2c. What factors govern the ability of a game development firm to create successful products?

This question looks at the situation from the viewpoint of the multitude of game ideas that go through a filtering process after which a small portion end up as hits. This view is complemented with the viewpoint of the development firm and its struggle to create a game that sells well. This problem is approached through the following research question:

Q2d. What factors limit the sales of a game product?

Questions 1a, 1b, 2a and 2c form a diagnosis of the evolution and the state of the games industry based on the concepts of industry life-cycle theory. Questions 1c, 1d, 2c and 2d explore the micromechanisms of the games industry that can explain the observed life-cycle dynamics. This is described in Figure 3.

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Figure 3. Positioning the research questions.

The research questions comprise two analytical steps. The first step is the diagnosis of the industry dynamics and the second step is to explain such findings with the micromechanisms. The methods used in each step are described in the following chapter.

Dynamics:

Diagnosis

Micromechanisms:

Explanations

Innovative activity Competitive process Q1a. Innovation patterns

Q1b. Interconnections

Q2a. Concentration Q2b. Ability to absorb

entrants

Q2a. Innovation process Q2b. Communication

Q2c. Limits to ability Q2d. Limits to sales

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4 Data and methods

The objective of the empirical enquiry is to examine the applicability of the concepts and propositions of the industry life-cycle theory in the analysis of the games industry. The review of the literature on cultural and creative industries gives an indication as to what can be expected to be found. Tschang (2007, p. 990) suggests that it may be that particular creative industries do not settle down to a dominant design followed by the era of incremental innovations as such industries are driven by the ongoing tension of creative innovative and rational business interests. Whether this is the case within the games industry, or something more complex, remains to be seen.

The empirical enquiry comprises two analytical steps. The first one aims at understanding the dynamics of game hardware and software sectors through the concepts and variables of industry life-cycle theory. The second step aims at understanding the micromechanisms of the game development industry through interview data and qualitative systems dynamics modelling. This way the observations of the industry dynamics can be explained through the micromechanisms that produce them. Comparable two-step approach has been used by Huygens et al. (2001), whose study on the music industry evolution comprised a historical study based on secondary sources and a multiple-case study based on interview data.