Riassunto analitico
Businesses in the digital age are constantly looking for innovative ways to stay competitive and adapt to quickly changing markets. The potential of digital twin technology in promoting business model innovation in the industrial automation sector is investigated in this thesis research. Businesses are looking for new methods to streamline operations, boost efficiency, and provide value-added services as the sector embraces digital transformation. By enabling the construction of virtual replicas of actual assets, processes, and systems, digital twin technology provides a viable solution that allows for real-time monitoring, analysis, and optimization. This research focuses on conducting a comprehensive case study analysis of a company that produces sensors and components for the industrial automation sector that has decided to adopt digital twin technology to drive business model innovation. The study examines the company's journey, exploring the challenges faced, strategies employed, and actual outcomes in terms of business model selection achieved through the adoption of digital twin technology. Through interviews, observations, and analysis of organizational documents, this research seeks to uncover the key drivers, enablers, and barriers to business model innovation facilitated by digital twin technology. It examines how the company leverages digital twin capabilities to create new value propositions, enhance customer experiences, and transform its revenue streams. The findings of the case study analysis will contribute to our understanding of the transformative potential of digital twin technology in the industrial automation sector. By examining a real-world example, this research aims to provide valuable insights and a starting guideline for other companies operating in the production of sensors and components for the industrial automation. The project will develop a conceptual framework for leveraging digital twin technology to drive business model innovation, offering guidelines for organizations seeking to adopt this technology and transform their operations. The implications of this research are significant for the industrial automation sector, as it provides a first roadmap for organizations to navigate the complexities of digital twin technology and utilize it as a catalyst for innovation. The study's findings will contribute to the emerging field of digital twin technology and its application in business model innovation. Ultimately, this research aims to inspire and guide organizations in the industrial automation sector to explore new avenues for growth, competitiveness, and sustainable success through the adoption of digital twin technology.
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