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Alberto Alvisi
Dept. of Management, University of Bologna, Italy
&
Marco Zamarian
R.O.C.K. Research on Organizations, Coordination & Knowledge Group,
Department of Management and Computer Science, University of Trento, Italy
Keywords: gaming industry, integration, focalization, strategic positioning, inter-firm cooperation, knowledge.
General description
The main goal of this paper is to show how relevant actors in the game industry follow a few, rather well defined, strategies for growth and learning. Focusing on publishing firms, in particular, we will show how these strategies can be thought of as the combination of choices over two dimensions: vertical integration and focalization.
In the second part of the paper we will investigate the relationship between different choices of strategic positioning over the two dimensions previously identified and performance. Moreover we will give a dynamic overview of how firms "migrated" through different solutions over time in order to achieve better performance levels.
We will interpret these trajectories and the relative performance levels of firms belonging to different clusters as attempts to gain and exploit new sources of knowledge to improve their capabilities. Namely, in this regard, we can identify two alternative routes of improvement.
The first one, that we can call "self-teaching", revolves around the idea that firms learn more and better building on their own previous knowledge. In this case firms will typically pursue a pattern of growth that is highly focalized on improving on capabilities that they already have, at least to some extent. They will tend to establish long term relationships with business partners and to stick to a few familiar game genres.
The second route, that stresses the need to incorporate knowledge from outside, is undertaken by firms who are typically less focussed but more flexible and adaptable.
Data
For this paper, we used a dataset that includes every software title for the Sony PlayStation published in Europe from September 1995 to December 2001 (source: Sony official data). The decision to focus on the Sony PlayStation instead of multi-platform games (i.e. including PC titles as well as other gaming consoles) is motivated as follows: The PlayStation, as most gaming platforms, has a closed architecture. This means that improvements over several gaming dimensions are mainly driven by learning, and not by hardware upgrades. The dataset is organized by "project", that is a single game title is our unit of analysis. For each title we collected data on publishing and developing firm, genre, date of release on the market.
Out of this population we selected a random sample of games. For the games included in our sample we proceeded to collect performance data. Performance has been defined as a complex construct derived from a linear combination of a measure of performance on the market in terms of sales and a measure of performance in terms of ratings received by reviewers.
Model and Methods
In order to answer to our first research question we build a taxonomy of different patterns of game production and development, along the two directions of integration and focalization. To keep the model simple, yet descriptive enough, we divide the game production process in two large blocks: "development stage" and "publishing stage". Each stage is conducted by an actor ("developer" and "publisher") and again, for simplicity's sake, we will concentrate on "publishers."
We will have maximum integration when a game "publisher" always develops its own games, as well. At the other end of the continuum we will have minimum integration when a game "publisher" never develops its games internally. The other dimension of our taxonomy, focalization, is defined as follows. A publisher is completely focalized when it only publishes games belonging to one genre. At the other end of the continuum we will have publishers who publish games belonging to every possible genre. The clusters of firms using alternative strategies at any given point in time are defined by measures of relative distance along these dimensions.
Evolutionary patterns and trends are identified through a comparison of these "snapshots" over time.
As far as the second of our research questions is concerned, we test the hypotheses regarding the relationship between different strategic choices and different levels of performance by means of linear regression models.
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