Business Academy SouthWest

Entrepreneurship is central to diversifying and enhancing the competitiveness of tourism offerings. The current literature underscores a critical oversight in nurturing entrepreneurship for tourism innovation and urges further exploration of entrepreneurial motivations in tourism start-ups. This is particularly relevant because the tourism sector heavily relies on new ventures to drive innovation, as established firms often struggle to meet the growing demand for distinctive and unique travel experiences. This study examines the entrepreneurial journey and innovation process within the tourism scene. Through comprehensive desk research and an in-depth entrepreneur interview, we aim to deepen our insights into the motivations driving entrepreneurs and the innovation processes behind their tourism products and services. Specifically, our research focuses on pop-up restaurants, illuminating their embodiment of innovation and lifestyle entrepreneurship. The findings reveal that a sense of freedom, creativity, and the pursuit of uniqueness stand out as key motivational factors of establishing pop-up restaurants. These motivations extend into a continuous business innovation cycle, as the drive to enhance and offer novel experiences remains paramount. This study elucidates the uncharted territory of tourism entrepreneurship and offers valuable insights into the driving forces and innovative dynamics within this evolving market.

The modeling and control of a 1-D magnetic levitation system with a permanent magnet object is investigated. The feature of the moving permanent magnet is explored using an experimental method and it is modeled through curve fitting technique. The entire system model is derived based on the electromagnetic theory and afterward system coefficients are identified through designed experiments. The developed model is validated through performance comparison of the closed-loop model and the controlled physical system. The PID control is chosen as the control structure at this stage regarding the fact: (1) it is simple and require few computation resources; (2) The developed PID controllers only need the position information, with no need for the current measurement and speed estimation, such that the potential degradation of the system performance due to quantization (Barie & Chiasson (1996)) can be minimized; The developed controllers are implemented in the LabView environment based on a PC running Windows XP. The real-time issues are managed by additional programs. Both simulation and real tests showed a clear consistency and a good system performance. Furthermore, The investigation of using genetic algorithms to automatically tune PID controller shows a potential to use this artificial intelligence method for supporting the control design for complicated nonlinear systems.