IEEE Global Communications Conference
9-13 December 2018 // Abu Dhabi, UAE
Gateway to a Connected World

WS-25: BMIIoT - Business Model Innovation (BMI) and Socio-Economic Impacts in IoT

WS-25: BMIIoT - Business Model Innovation (BMI) and Socio-Economic Impacts in IoT

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The workshop has been merged with the workshop on Computational intelligence and big data towards trustworthy IoT and the workshop on Collaborative intelligence for big data. For the new programme, please see the page for CIBDIoT.

The workshop aims to describe the complex interplay of IoT technology invention and the business model innovation (BMI) associated with the utilization including socio-economic aspects identified with the tool Tussle Analysis (TA). Besides keynote and presentation of interdisciplinary studies BMI and TA methods will be applied in a hands-on session.

The interdisciplinary studies of interest include but are not limited to:

1. Case studies and longitudinal studies of BMI in IoT: Position papers describing the usage of IoT and business models innovation (BMI) methods used for developing the businesses and the related innovation processes. This also includes the driving stakeholders (e.g., developers, standardization organs, industry, end-users) influenced by targeted market and audience,  business development, education, legislation, ethics, development cycles and theory.  

2. Evaluation of IoT application and innovation in terms of business potential: With focus on the IoT technology in the business models both in the innovation and the development  stages and on business models in the market. How does the evaluation progress and how is the evaluation done or altered compared to previous. 

3. Socio-economic impacts of IoT: With focus on IoT platforms and frameworks that improve life and interact with the environment having consequences with  high influences on existing solutions, technologies, and businesses.

4. IoT technology influences in business models for different sectoral: Studies describing IoT technology utilized in different ways across different sectors. Also studies describing the influence of deployed IoT technology in the same sectors or business models. Setting-up new interactions in existing ecosystems and the emergence of new ecosystems upon the deployment of IoT technology.

5. Cross-sectoral learnings on the adoption of IoT technology and inventions: Adoption of IoT and data driven business models moving across industry sectors showing significant learning. The use of cases and real implementations as well as studies giving evidence of performance and accuracy of solutions.


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