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Climate change is currently one of the biggest challenges both in terms of danger to natural habitats, wildlife, and humanity. To tackle climate change, we need to reduce our carbon emissions in a fast and decisive way. This thesis studies one of the potential solutions to do so: green hydrogen. More specifically, its potential development by 2030 in Spain using INKA 4.0 scenario planning software.
Green hydrogen shows to have a wide range of applications, from transport to heating and industry with great potential to decarbonize many sectors. It does come, however with a number of important hurdles mainly related to cost, scalability and technical difficulties that will need to be addressed for it to be successful. With this, 10 descriptors were created generating three scenarios to be studied. The most consistent of them, a successful development of green hydrogen in Spain by 2030 is characterized by having all of its descriptors in a favoring state while the other two have some or all in a hindering state, making its development not successful within the established timeframe. Concluding that due to the great challenge the development of green hydrogen is, its success needs to have all factors supporting it.
The sector of supply chain risk management has been expanding for several years now, with the goal to not only prepare organizations to recover after supply-chain disruptions but also mitigate risks to reduce losses.
One of the most remarkable techniques in the field is the Artificial Intelligence technology, which owing to its effectiveness and efficiency, allows humans to develop new solutions to predict or prevent a great variety of supply-chain disruptions.
This paper aims to forecast the future state of the Artificial Intelligence technology in Europe by 2035 with the use of the INKA 4 scenario manager software. A total of four areas of influence –– i.e., technological, financial, legal, and social –– were identified.
From those, 11 descriptors were created based on relevant scientific literature and were inserted in the INKA software to develop the scenarios. This process resulted in three clearly differentiated scenarios that exhibit high probabilities and positive outlook for the Artificial Intelligence technology to be widely integrated in supply chain risk management systems in Europe by 2035.
Scenario Planning: How is big data going to influence the future of smart mobility in Germany?
(2016)
Smart mobility is the future of transportation services in Germany. The implementation and management of smart mobility is impossible without using big data. At the present time,the analysis of big data in Germany is not fully implemented due to existing challenges. The purpose of this research project is to forecast the impact of big data on smart mobility in Germany with the use of scenario planning. In order to receive the most actual scenarios, the input factors were designed in accordance with extensive literature research, and then ratios between all specifications of input factors were compared and evaluated. Thus four unique scenarios were selected for further detailed interpretation to suggest possible influences of big data on smart mobility in Germany