Companies within the high-technology industry are largely dependent on a specialised knowledge base to make advances in technological innovations and maintain a competitive advantage. Technology start-ups (TSUs) have limited resources and face various organisational challenges which place them at a disadvantage in the recruitment of skilled knowledge workers. This research investigates the factors which attract highly skilled knowledge workers to technology start-ups (TSUs) in South Africa, despite their numerous challenges. This study used a mixed method design involving 129 knowledge workers. Exploratory interviews were conducted in the first phase to investigate which factors attracted knowledge workers to TSUs. An Adaptive Choice-Based Conjoint (ACBC) experiment in the second phase tested the relative importance of the attributes that were identified during the interviews and in the literature. The findings revealed that intellectual challenge and financial package were the most important individual attributes while non-financial job attributes were most important overall. Different preferences existed between genders although not between job types. The entrepreneurial aspirations of the knowledge worker were also found to be a significant factor in their attraction to a TSU. Recommendations are made to TSUs for recruiting talent based on the findings.Copyright / Dissertation (MBA)--University of Pretoria, 2011. / Gordon Institute of Business Science (GIBS) / unrestricted

No / Purpose - The aim of this paper is to gain a better understanding of how small technology start-ups learn about a key customer in the context of B2B relationships, and to propose a model of interfirm learning with customers. Design/methodology/approach - Using a qualitative case-based approach, the authors immerse themselves in the development of three learning alliances between technology startups and industry leaders, two successes and one failure, to gain an in-depth understanding of the dynamics involved. Data were collected on both sides of the alliance dyad. Findings - The paper delineates four learning cycles: alliance inception, joint-learning, specialization and discovery. These learning cycles constitute sequences of increasing understanding, cooperation, and higher order learning between the partners; evolving from an exchange of existing knowledge to the joint development of new knowledge. Originality/value - This study contributes to an integration of the alliance and marketing literatures by offering empirical evidence of a different type of alliance, namely the reciprocal learning alliance. It also contributes to broadening our understanding of market orientation in inter-organizational settings. In the context of business-to-business relationships, the study has identified four critical dimensions of learning alliance success, and proposed how they could be measured: Learn about customers; Interact with customers; Customer-specific investments; and Co-develop breakthrough innovations. Finally, the study demonstrates the significant role played by 'committed champions'.

Background: In today's digitalized and globalized business environment, entrepreneurs are constantly challenged to carefully plan its start-ups products, services or business model. Any failure in one of those components may result in a less competitive company, which could lead to failure as consequence. Business model is often seen as a central and important part of a start-up. Over time, entrepreneurs look for new ways of improving its current business model or new ways doing business always aiming economic growth. Business Model Innovation is a technique that supports companies, business managers and entrepreneurs to look for business opportunities (or business models) that would somehow be related to the company. Purpose: The main purpose of this master thesis is to expose the challenges that start-ups face in terms of business model and then to understand how the companies studied overcame those challenges by making use of business model innovation (BMI). We also look to understand what kind of impact business model innovation generated in the start-up, in terms of economic growth. Method: Primary data and secondary data were collected through qualitative semi-structured interviews involving multiple case study of five technology start-ups in Sweden. Once all data were collected and stored, we made use of open and axial coding techniques in order to perform data analysis to possibly generate a theory and the answer to the research questions. Conclusion: All start-ups are aware about the importance and positive benefits that business model innovation could bring. When it comes to challenges, there are two main problems, where the first one is related about the difficulty to abstract different business model and then incorporate into the company’s context while the second one is once they manage to overcome the first challenge, they still needs to find a way to make sure it would be profitable. Another finding is that older start-ups tends to be more aware about the positive and negative impacts that business model innovation could bring, and each company has its own method to validate a business model innovation. We analyzed each case, identified some patterns and develop a model that helps start-ups to validate potential business models to be incorporated in the company.

This study explains the rise and fall of the Innovations Foundation, the University of Toronto's first office dedicated to the transfer of university-developed technologies to industry. Drawing on extensive archival research, ten interviews with key informants, and other sources, the case study traces the evolution of the Foundation from its launch in 1980 to its closure in 2006. The study delineates three distinct business models under which the Foundation operated from 1980 to 1990, 1990 to 1999, and 1999 to 2006. The reasons for the adoption and failure of each model are explored and a historically grounded, context-sensitive explanation of the university's decision to dismantle the Foundation in 2006 is provided. This explanation emphasizes the importance of managing unrealistic expectations for Canadian university technology transfer, and adds weight to a growing consensus on the importance of historical path-dependence as a conceptual tool for understanding the persistence of differentials in technology transfer performance among universities.

This study explains the rise and fall of the Innovations Foundation, the University of Toronto's first office dedicated to the transfer of university-developed technologies to industry. Drawing on extensive archival research, ten interviews with key informants, and other sources, the case study traces the evolution of the Foundation from its launch in 1980 to its closure in 2006. The study delineates three distinct business models under which the Foundation operated from 1980 to 1990, 1990 to 1999, and 1999 to 2006. The reasons for the adoption and failure of each model are explored and a historically grounded, context-sensitive explanation of the university's decision to dismantle the Foundation in 2006 is provided. This explanation emphasizes the importance of managing unrealistic expectations for Canadian university technology transfer, and adds weight to a growing consensus on the importance of historical path-dependence as a conceptual tool for understanding the persistence of differentials in technology transfer performance among universities.