Purpose -This paper seeks to add to our understanding of how entrepreneurs can build "knowledge reservoirs" to achieve competitive advantage. The study focus upon the following issues: what kind of actors can be found in various entrepreneurs' knowledge reservoirs, and what business knowledge do these actors possess. Design/methodology/approach -The author employs a longitudinal case study approach, involving a sample of seven entrepreneurs in new technology-based firms, each interviewed two times during the period from 1999 to 2001. Findings -Evidence suggests that entrepreneurs should build knowledge reservoirs, segmented into internal, semi-internal and external knowledge reservoirs. These reservoirs should be a means to gain competition advantage.Research limitations/implications -The conceptual model has both empirical and theoretical backing, but the empirical backing is limited to seven cases. It would be useful to test the conceptual model on larger sample sizes. Practical implications -Practitioners can focus on how to build knowledge reservoirs, while the model helps to increase awareness of the holistic view of entrepreneurial knowledge and which actors can contribute to it. Policy makers should encourage entrepreneurs to build knowledge reservoirs, and support systems could require a plan for this activity before entrepreneurs get access to public funds. Originality/value -The paper makes four main contributions: model generation, development of terminology, further development of the field of entrepreneurial research, and development of RBT.

PurposeDuring the last decade, there has been an increasing focus on commercialization of knowledge and technology from universities. However, universities report financing as being the main impediment to successful university spin‐off companies (USOs) creation, leaving valuable inventions un‐commercialized. The purpose of this paper is to develop a conceptual model in order to explain financing challenges experienced by USOs.Design/methodology/approachThis paper presents a conceptual model illustrating financing challenges met by USOs, and provides an explanation why TTOs report that obtaining financing is their biggest impediment to spin‐off creation. Two different theoretical perspectives back this conceptual development: Knightian uncertainty and agency theory.FindingsThis theoretical examination suggests that increasing levels of uncertainty affect the investor's willingness to fund new companies in a negative way. Through the literature review, clear indications were also found for the increased uncertainty with which USOs are faced. It is therefore natural to conclude that investors are more reluctant to invest in USOs because of the level of uncertainty compared with other entrepreneurial companies.Research limitations/implicationsThis study made a generalization of USOs as a homogeneous group of companies, which is an oversimplification. Further research should address how different business models, types of resources and their institutional link affect USOs' capital requirements and their problems in raising the required capital.Originality/valueThe main contribution from this paper is the combination of theoretical insights from the concepts of Knightian uncertainty and agency theory. These combined with insights from previous empirical studies explain why USOs face specific challenges in order to raise risk capital.

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Business growth through intentional and non-intentional network processes AbstractPurpose. The purpose of this paper is to examine business growth and explore the "growth mode" among 24 women entrepreneurs participating in a development and networking programme conducted within a Nordic research project.Design/methodology/approach. A longitudinal design with an inductive methodology driven by empirical findings made it possible to follow entrepreneurial growth as an unfolding and emerging process. The analysis is structured following established procedures for inductive theory-building research using guidelines for constant comparison techniques and worked recursively between the data and emerging theory.