Technology Entrepreneurship

New Technology-Based Firms (NTBFs) learn their business in the early-stages of their life-cycle. As a central element of the entrepreneurial learning process, the business model describes the value-creation functions that are conceptualized in different stages of the NTBF’s life-cycle. Transaction relations connect the model with the business reality and ideally mature in strength over time to a functioning value-network. This chapter describes the development of a research design that determines, extracts, and evaluates semantics constructs of this entrepreneurial learning out of a convenient sample and three cohorts of business plans submitted to a business plan award between 2008 and 2010. The analysis shows empirical evidence for the survival and growth of those NTBFs that exhibit a balanced status of entrepreneurial learning in the maturity of the value-network that can be characterized as early startup-stage. The empirical findings of the network theory based business plan analysis will allow for a better explanation of the performance in the entrepreneurial process that is discussed for NTBFs based on theory of organizational learning.

This chapter develops a framework for analyzing the architecture of technology ventures. The framework is based on the concept of business model-how the venture creates and captures value. Application of the business model concept in the technology venturing literature results in four theoretical postulations which explain how and why technology ventures differ from other ventures. In summary, we propose that: (1) business model of technology ventures has a complex technological core and a flexible marketing periphery. (2) Because of this core-peripheral architecture, business model of technology ventures is technology-driven and market-driving (3) market driving-ness makes these business models disruptive and (4) versatile, able to tap into multiple emerging markets. Supportive empirical evidence from three technology ventures substantiates this framework and its implications.

In the process of development of new technology-based firms (NTBFs), the crucial role belongs to establishing an effective and efficient business model to deploy the focal technology in a sustainable way. As such, it becomes clear that the business model design and testing/validation become the essential parts of a startup process; yet, so far, the topic of the business model in the context of NTBFs has received insufficient attention in the literature. Drawing on the basic theoretical and empirical insights from entrepreneurship and strategy research, this chapter scrutinizes the topic of the ontological nature of a firm’s business model within the NTBF context, and its relatedness and distinction from strategy, technology, and innovation. From definitional issues, we proceed to discussing the role of the business model in the process of development of NTBFs. Then, we summarize the available empirical material to formulate the most frequently occurring problems with new ventures’ business models that prevent their development, paying particular attention to ways of preventing and dealing with such problems. The developed conceptual framework of business model-related NTBF challenges is illustrated and corroborated with the mini-cases of technology ventures.

New product development (NPD), as a locus of the innovative potential of organizations, plays an essential role in small technology-driven company survival. To address the research gap and fulfill the companies’ needs, this survey aims to post and verify a new, simple and not time-consuming methodology for risk identification and categorization of industrial products development. To check the hypothesis that NPD project technical, cost and schedule sets of risks could be categorized as both threats and opportunities, an experiment was conducted in a small Serbian enterprise that has developed 52 innovative solid state based lighting products for outdoor lighting infrastructure. There were 69 identified risks (51 threats and 18 opportunities) that through 76 factors influence new products’ technical characteristics, schedule and cost. Explorative factor analysis was applied to reduce and compress the data and 26 composite factors were obtained as valid predictors of the NPD project results. Regarding the technical characteristics risks, the threats can be grouped into four factors consisting of six risk types, while opportunities can be grouped into two factors consisting of four risk categories. The risks influencing the schedule disturbance that act as threats are grouped into eight factors consisting of ten risk types, while those that could be used in opportunities are grouped in four factors with eight risks identified. The risks influencing the costs that threaten the project are recognized as five factors described by seven risks, while those that act as opportunities are grouped into three factors described by five variables in total.

This chapter examines the application of the Effective Innovation Leadership (EIL)-Model in the Information and Communication Technology (ICT) practice. The EIL-Model was the outcome of a study grounded in the iteration of six different data sources. In this chapter, the focus lies on insights taken by applying the EIL-Model within three German DAX-companies from different industries. The study leads to a better understanding of the EIL-Model components and reveals that seven sub categories are dominantly affecting the effectiveness of innovation leaders. Those sub categories are openness, trust, delivery, association, perseverance, entrepreneurship, and focus.

The process of commercializing new technologies, i.e. of creating technology push innovations, is poorly understood and modeled in very different and heterogeneous ways in the academic literature. Furthermore, no framework exists up to now to allow for practical facilitation like Design Thinking supporting user-centric innovations. To tackle these shortcomings, this chapter aims to improve the understanding of the technology push process and take initial steps towards a practical methodological framework. The understanding is enhanced by creating a consolidated and unified model of the process which builds on a systematic literature review. Additionally, methods are identified, evaluated and combined into a workshop format for the most critical phase of technology application selection. A case example in a university setting shows that the workshop is well-suited to advance technologies. Both the process model and the workshop concept are relevant for the academic and practical contexts: The process model aids in better understanding the technology push process and unifies different views. The workshop is an essential first step in designing a systematic framework for practical technology push developments with concrete methods and tools. The methodology is new to the field of innovation management and forms a well-designed starting point for similar endeavors.

This study analyzes the effects of regional- and firm-level factors on the intellectual property (IP) output of high-tech firms. So far, little is known on how regional factors influence the IP output of high-tech firms. We combine data on 8317 German high-tech firms with regional data and perform various regression analyses. We measure the IP output by the number of granted patents and trademarks. In particular, the receipt of venture capital and firm size have a significant effect on the IP output. With regard to regional factors, the student rate in a region is positively linked to IP output, whereas the existence of a technical university in a region has no significant effect on the IP output. Implications for policy makers and practitioners are discussed.

While they boost the economy and innovation, New Technology-Based Firms (NTBF) frequently experience difficulties to finance themselves. In Europe, policy makers react by providing them with grants. However, three elements cast doubt on these grants. First, it has been argued that most NTBF financing constraints would be due to the immaturity of projects rather than the lack of investors. Second, Pecking Order Theory suggests that grants, being free and non-dilutive, may be solicited without actual financing constraints. Third, the ability of grants to help their beneficiaries pursue commercial and financial development has been questioned. We contribute to these conversations by answering three research questions: (1) Are grants to NTBF answering to supply-sided financing constraints? (2) Why do NTBF apply for grants? (3) Are grants signaling NTBF to investors? We address these questions by studying the financing path of eight grant-supported NTBF during 3 years after incorporation through case studies. Our findings may be grouped around three themes. First, supply-sided financing constraints exist but are rare. Most of the time, firms attracted equity if they wanted to do so. Second, opportunism and the will to limit dilution support the overwhelming majority of grant applications. Third, we do not observe a certification effect from grants to investors. It rather seems that having attracted outside investors or promising first sales play an important role in obtaining or increasing grant support.

The Chapter is focused on the analysis of the educational and state-support policies as the main drivers of the successful development of ICT sector in Belarus. It contributes to the existing literature on ICT ventures development in Central and Eastern European countries in general and on ICT industry in Belarus in particular. The research is mainly targeted to the academic audience (students and faculty), although the practitioners (VC and businesses looking for the offshore outsourcing destinations) could gain some useful insights from this research, as well.

The traditional vision of the university as a teaching institution still prevails in many countries. Typical of this vision is the high-risk aversion to knowledge commercialization due to lack of institutional support and market knowledge. Therefore, university scholars and seem more interested in publishing and graduates are more interested in secured life-time employability instead of commercialising their research and ideas on the market which does not contribute to technology transfer (TT) process and economic growth.

This chapter aims at providing insights into the important success factors of creation of academic spin-offs and entrepreneurial university, by carrying out a systemic review of eclectic literature on knowledge commercialization a technology transfer. It reveals that technology transfer offices (TTOs), centres for entrepreneurship and entrepreneurship education as important success factors for academics spin-offs and knowledge commercialisation. Practical implications for entrepreneurship university and other stakeholders and discussed.

This chapter focuses on different approaches and methods aiming to optimize the institutional framework for academic-spin-offs in the different stages of the entrepreneurship process. A brief description of the main argument, the establishment of an Entrepreneurial University, will enable a better understanding of its complex structure and will provide an insight into the mutual interdependencies in the spin-off value chain. Research-intensive spin-offs generated by universities and research centers are one of the most important innovation motors and the vehicle for disruptive innovations. The large number of scientific results and inventions that frequently remain passive assets of the universities in the form of intellectual properties, could create an enormous potential for starting successful and sustainable enterprises. Besides creating new ideas and innovations, a key factor for success is an appropriate institutional framework along the whole spin-off value chain. A permanent and sustainable Entrepreneurship Culture requires a holistic Entrepreneurship Governance throughout the entire transformation process, from research to the marketable product.

In the following chapter the authors will analyze the concept of the Entrepreneurial University and describe the characteristics of Entrepreneurship Governance which may accelerate the process of knowledge-based spin-offs in the universities and research centers. The authors will rely on empirical findings in leading entrepreneurial universities and show how an overall entrepreneurship institutional framework may function. In a next step institutional requirements for each stage of entrepreneurship process will be discussed and the determining factors will be described.

Within their activities in research and teaching, universities generate significant resources for creation and invention processes. Unfortunately, inventions often cannot be transformed into innovations, and therefore lack the market commercialisation. Reasons for that might be missing resources of universities for further prototyping and testing ideas. At this point, also known as ‘Valley of Death’, the main university task (namely conducting research) ceases, and as a result entrepreneurial potential remains unexploited. This chapter elaborates on two possible options how to overcome the ‘Valley of Death’. In a first step, several aspects of potential resources and their meaning for an innovation process are derived from literature. German entrepreneurship initiatives, which are explored empirically through their business models in order to gain an insight of how invention processes are supported, could be one option. A second option may be private start-programs like venture capital and corporate incubation that approach the innovation process from a commercialised perspective. The findings indicate that university initiatives have to shift their finances in order to sustain their start-up activities. In this context, the role of public private partnerships seems to be a viable option to be discussed.

A driving force in the creation of new firms resides in the developments of novel technology by members of current companies. When this happens, an employee gains the incentive to quit the parent company and start a new business venture (i.e. spin-out). Research on entrepreneurial employees and their spin-outs is fragmented and misleading. This chapter finds theoretical gaps and enlarges the understanding of the conditions that allow technological knowledge to give rise to entrepreneurial employees. The analysis of 23 entrepreneurs and 10 spin-out companies in the internet and bio-tech industries shows the pattern of creation of new technological enterprises. It recognizes the role of employees’ entrepreneurship in the formation of innovative ventures. Eventually, the new technology moves again when an existing company acquires the spin-out along with the entrepreneur. This research solves conflicting views in the literature and gives insights into how entrepreneurs actively transfer technologies from one company to another. Entrepreneurial employees create new ventures in a different industry, combine multiple experiences in mature businesses, and pursue acquisition. These conclusions push scholars and practitioners to look at employees’ accumulation of knowledge and business experience as a source of innovation.

The economy of the twenty-first century is driven by digitalization of markets, industries and companies, accelerating innovation cycles and a worldwide rise of young ambitious talents that grow their own start-ups. Many established companies face major challenges in the area of innovation, organization or corporate culture.