Common use of Research Methodology Clause in Contracts

Research Methodology. ‌ To analyse the growth processes of technology-based new ventures I conducted a survey among entrepreneurial firms. Due to the large sample size, this method is usually very reliable and enables the researcher to generalise the corresponding findings. The survey in this study has a longitudinal design. This design allows me to track the evolution of dynamic capabilities in a larger sample of entrepreneurial firms as discrete events over time. The survey population comprises a set of German technology-based new ventures that survived a predefined observation period and thus are ex ante considered as successful. All sample firms are located in one region. By focusing on a certain geographical area, I eliminate environmental influences such as infrastructure, access to labour markets, educational and scientific institutions, government support, etc. These effects often have a significant impact on the evolution of start-up firms and may inhibit the comparability of the sample companies. To ensure a large population of entrepreneurial ventures, I chose an innovative cluster for the survey. Innovative clusters facilitate regional entrepreneurial activity (▇▇▇▇▇▇▇▇▇, ▇▇▇▇▇▇▇▇▇▇▇, and ▇▇▇▇▇▇▇▇ 2001). In fact, entirely new industries such as semiconductors, biotechnology, microcomputers, or information and communication technologies have developed in specific geographic regions (▇▇▇▇▇▇▇ 2001). A major source for the foundation of new firms is tacit knowledge. This knowledge is usually developed in regional clusters and cannot be diffused easily across geographic areas (▇▇▇▇▇▇ and von ▇▇▇▇ ▇▇▇▇; ▇▇▇▇▇▇▇▇▇ and ▇▇▇▇▇▇ 2001). The entrepreneurial activity within the cluster is mostly determined by its regional strength (Sternberg 1996). This strength is often influenced by the existence of active research universities, strong local networks, and venture capital (▇▇▇▇▇▇▇ 2001). A region with high entrepreneurial activity is the area around Munich. It is considered as “the heartland of the entrepreneurial régime” in Germany (▇▇▇▇▇▇▇▇▇ and ▇▇▇▇▇▇▇ 2002, p. 117). In particular, the biotech cluster at Martinsried, a Munich suburb, still constitutes a major European centre for life sciences (Lehrer and ▇▇▇▇▇▇▇ ▇▇▇▇▇; Lehrer and ▇▇▇▇▇▇▇ 2004b). Thus, I decided to limit the population of this study to technology-based new ventures in the Munich region. To show the evolution of dynamic capabilities in technology-based start-ups, the observation period starts with the foundation of the company. However, to ensure a certain quality of data, I limited the time of observation. Otherwise, early observations could easily have been biased or entirely lost. To be able to nevertheless cover as many phases of the growth process as possible I focused on high-growth companies. In general, VC funding accelerates growth rates in entrepreneurial firms (Davila, ▇▇▇▇▇▇, and ▇▇▇▇▇ 2003). Consequently, I limited the population to companies that have received venture capital funding. Thus, I expect to observe more phases of growth than in companies that have not received any financial support from venture capital firms. For the survey, I adopted a longitudinal, multi-method, multi-case field research design, which is in line with ▇▇▇▇▇ and ▇▇▇▇▇▇▇'▇ (1992) propositions for entrepreneurial research. The approach relies on qualitative and quantitative data. The data includes questionnaires and semi-structured interviews. In addition, I collected information from a commercial database on venture capital funded companies and from public sources such as company web pages or press releases. The multi-method design increases the quality of the research and allows for triangulation (Davila and ▇▇▇▇▇▇ 2005). In fact, triangulation (Jick 1979) is an important criterion for the constructivist research process (Tacconi 1998). The multi-case field design allows me to gather a sample that is large enough to examine whether certain findings can be generalised by applying statistical methods. Thus, the research is not limited to company-specific experiences.