Predictive survivability model of technological start-ups: a case study of Smart Parking

Abstract

The dissertation focuses on analysing pre-existing survivability prediction models that can be applied to new businesses and start-ups. After studying certain popular models and their critical success factors that can be found in successful businesses and are lacking in failed businesses a new prediction model for technological companies will be crafted. Furthermore, a case study of a potential technological start-up company called Smart Parking will be internally and externally analysed with regards to the environment in will be operating in. The analyses of the internal and external environments will help plan and come up with business strategies for Smart Parking. With the complete view of business analyses and planning, a conclusive report on the survivability of such a start-up will be drafted. Finally, after internal and external analyses of Smart Parking, the critical success factors of Smart Parking will be run through the new survivability prediction model to predict the survivability of the technological start-up Smart Parking. The thesis covers previous similar topics covered and the gaps identified thereby providing a thesis statement and an approach to the dissertation methods. It also covers the significance of such a research and its deliverables while keeping in mind the limitations of the research