The rise of a new cultural products industry cluster in Germany : the case of the Leipzig media industry
Bibliographic record
Abstract
Over the past decade, a variety of studies have shown that other sectors in addition to high technology industries can provide a basis for regional growth and income and employment opportunities. In addition, design-intensive, craft-based, creative industries which operate in frequently changing, fashion-oriented markets have established regional concentrations. Such industries focus on the production of products and services with a particular cultural and social content and frequently integrate new information technologies into their operations and outputs. Among these industries, the media and, more recently, multimedia industries have received particular atte ntion (Brail/ Gertler 1999; Egan/ Saxenian 1999). Especially, the film (motion picture) and TV industries have been the focus of a number of studies (e.g. Storper/ Christopherson 1987; Scott 1996). For the purpose of this paper, cultural products industries are defined as those industries which are involved in the commodification of culture, especially those operations that depend for their success on the commercialization of objects and services that transmit social and cultural messages (Scott 1996, p. 306). Empirical studies on the size, structure and organizational attributes of the firms in media-related industry clusters have revealed a number of common characteristics (Scott 1996; Brail/ Gertler 1999; Egan/ Saxenian 1999). Most firms in these industries are fairly young, often existing for only a few years. They also tend to be small in terms of employment. Often, regional clusters of specialized industries are the product of a local growth process which has been driven by innovative local start-ups. In their early stages, many firms have been established by teams of persons rather than by individual entrepreneurs and have heavily relied on owner capital. Another important feature which distinguishes these industries from others is that they concentrate in inner-city instead of suburban locations (Storper/ Christopherson 1987; Eberts/ Norcliffe 1998; Brail/ Gertler 1999). In this study, I provide evidence that the Leipzig media industry shows similar tendencies and characteristics as those displayed by the multimedia and cultural products industry clusters in Los Angeles, San Francisco and Toronto, albeit at a much smaller scale. Cultural products industries are characterized by a strong tendency towards the formation of regional clusters despite the fact that in some sectors, such as the multimedia industry, technological opportunities (i.e. internet technologies) have seemingly reduced the necessity of proximity in operations between interlinked firms. In fact, it seems that regional concentration tendencies are even more dominant in cultural products industries than in many industries of the old economy . Cultural products industries have formed particular regional clusters of suppliers, producers and customers which are interlinked within the same commodity chains (Scott 1996; Les- 2 lie/ Reimer 1999). These clusters are characterized by a deep social division of labor between vertically-linked firms and patterns of interaction and cooperation in production and innovation. Within close networks of social relations and reflexive collective action, they have developed a strong tendency towards product- and process-related specialization (Storper 1997; Maskell/ Malmberg 1999; Porter 2000). In the context of the rise of a new media industry cluster in Leipzig, Germany, I discuss those approaches in the next section of this paper which provide an understanding of complex industrial clustering processes. Therein socio-institutional settings, inter-firm communication and interactive learning play a decisive role in generating regional innovation and growth. However, I will also emphasize that interfirm networks can have a negative impact on competitiveness if social relations and linkages are too close, too exclusive and too rigid. Leipzig's historical role as a location of media-related businesses will be presented in section 3. As part of this, I will argue the need to view the present cluster of media firms as an independent phenomenon which is not a mere continuation of tradition. In section 4 the start-up and location processes are analyzed which have contributed to the rise of a new media industry cluster in Leipzig during the 1990's. Related to this, section 5 will discuss the role and variety of institutions which have developed in Leipzig and how they support specialization processes. This will be interpreted as a process of reembedding into a local context. In section 6, I will discuss how media firms have become over-embedded due to their strong orientation towards regional markets. This will be followed by some brief conclusions regarding the growth potential of the Leipzig media industry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".