How can Zuyd University promote knowledge sharing between different departments and locations, and what structures are needed to enable the knowledge sharing?
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In this dissertation Maarten ter Huurne investigates why users in the sharing economy trust each other.
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Property sharing is one of the most prominent examples of the rapidly expanding sharing economy. Travelers around the world often opt to stay at a stranger's apartment instead of any other tourism accommodation. Trust is essential in this choice, because staying with, or taking in, strangers can entail great risks. To create trust between users, sharing platforms often promote a sense of community. However, the relation between sense of community and trust in the sharing economy is still largely unknown. To investigate this relation, both hosts and guests of two sharing platforms, namely Airbnb and SabbaticalHomes, were surveyed. The findings indicate that sense of community indeed enhances trust between users. Moreover, the evidence suggests that hosts have a stronger sense of community than guests. Also, a significantly higher sense of community was found on the platform where identification between users is higher. This study shows that affect for the community contributes to the understanding of trust in the sharing economy.
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The maximum capacity of the road infrastructure is being reached due to the number of vehicles that are being introduced on Dutch roads each day. One of the plausible solutions to tackle congestion could be efficient and effective use of road infrastructure using modern technologies such as cooperative mobility. Cooperative mobility relies majorly on big data that is generated potentially by millions of vehicles that are travelling on the road. But how can this data be generated? Modern vehicles already contain a host of sensors that are required for its operation. This data is typically circulated within an automobile via the CAN bus and can in-principle be shared with the outside world considering the privacy aspects of data sharing. The main problem is, however, the difficulty in interpreting this data. This is mainly because the configuration of this data varies between manufacturers and vehicle models and have not been standardized by the manufacturers. Signals from the CAN bus could be manually reverse engineered, but this process is extremely labour-intensive and time-consuming. In this project we investigate if an intelligent tool or specific test procedures could be developed to extract CAN messages and their composition efficiently irrespective of vehicle brand and type. This would lay the foundations that are required to generate big data-sets from in-vehicle data efficiently.
For the development of a circular economy and the reduction of the environmental impact of supply chains, the sharing of reliable information throughout the entire chain is a prerequisite. In practice, this is difficult to realise which blockchain can improve. BCLivingLab aims to explore the application of blockchain technology in supply chain and logistics. The project develops four physical hubs and a virtual repository for blockchain knowledge to support SME’s in developing use-cases and experiment with blockchain applications. The ambition is to build a community of interested stakeholders and to be involved in current and future blockchain initiatives.
For the development of a circular economy and the reduction of the environmental impact of supply chains, the sharing of reliable information throughout the entire chain is a prerequisite. In practice, this is difficult to realise which blockchain can improve. BCLivingLab aims to explore the application of blockchain technology in supply chain and logistics. The project develops four physical hubs and a virtual repository for blockchain knowledge to support SME’s in developing use-cases and experiment with blockchain applications. The ambition is to build a community of interested stakeholders and to be involved in current and future blockchain initiatives.
