In the field of entrepreneurship research, life cycle models are often used to describe the entrepreneurial process. These models are also used in research into growth problems. Kazanjian and Drazin (1980), for example, developed a four-phase growth model, and identified the typical growth problems of fast-growing firms in each phase.
Phase 1, Concept and development: Focus on the invention and development of a service or product. Main problems:
- developing the idea
- testing a prototype
- finding investment support for the idea
Phase 2, Commercialization: Developing the product for introduction to the market. Main problems:
- setting up the organization and production
- solving technical problems
- market entry
Phase 3, Growth: The fast-growth phase is characterized by its focus on the market.
Main problems:
- Producing larger quantities
- Guaranteeing quality
- Expanding market share
- Personnel problems
Phase 4, Stability: In this phase the focus lies on consolidating the market position with the initial product, and developing further products.
Main problem:
- Simultaneously managing the market entry of new products without losing the competitive advantages of older products.
Although life phase models like these can help the decision-making process in research and practice, they also have their pitfalls. In a review of such models, Sexton and Bowman/Upton (1991) warned that economic phenomena cannot always be compared to biological phenomena (life cycles). Firm growth does not always develop through the phases of such models in a straightforward, linear way, for example. Particularly in fast-growing industries involving technological change, growth is more chaotic than ordered. Moreover, well-known growth models with a bell-shaped, concave, or plateau structure are only useful as ideal reference patterns for actual growth processes.
Building on this criticism, Covin and Slevin (1997) suggest another growth model from the complexity management perspective. This model emphasizes that growth occurs through certain market factors in combination with internal competences and resources. The main problem for entrepreneurs is overcoming the increasing organizational and external complexity. In the following sections of this chapter we will define possible strategies for start-up growth. See Figure 15.2 below.
Industrial change is often triggered by technological changes, for which there are many examples: the substitution of digital technologies in a whole range of analog products, from office equipment to telephones, and the Internet as a communication medium. Technological changes like this enable start-up firms developing new technologies and introducing them to the market to take over the positions of their established competitors.
A second catalyst for industrial transformations is change in consumer behavior. The increasing technological competence of customers, for example, has enabled the growth of direct computer sellers like Dell. Customers are prepared to get information about even high-technology products from the Internet and order them online instead of asking for advice in a shop.
Deregulation or liberalization can also be a reason for industrial transformation and change. In recent years industry deregulation has created opportunities for start-up firms and growth opportunities in general in various industries, such as the air traffic, telecommunications, or financial service sectors.
Changes in technologies, customer preferences, or regulations offer opportunities for transformation and change, but it is up to entrepreneurs to make use of them. At the beginning of a transformation period, firms must experiment with different strategies to tap the growth potential of the industry situation. We have seen many different such experiments with Internet technologies in the last few years. Many of them came to nothing, but several successful business models have survived. We have already given the example of Dell as a successful direct provider of PCs via the Internet. Further examples are US company Auto-By-Tel’s sale of cars to traditional car dealers via the Internet, or E-Bay, the Internet auctioneers.
A period of experimentation is followed by a stabilization phase. In the literature, innovation management researchers talk about “dominant designs”. A dominant design stabilizes a particular industry structure, and the positions of competitors. There is generally a consolidation phase in the industry, and failed experiments lead to certain firms disappearing from the industry. However, successful business models can mean even faster growth for the survivors, as they can take over shares of the market from other competitors.
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