5 research outputs found

    BlockNet Report: Exploring the Blockchain Skills Concept and Best Practice Use Cases

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    In order to explore the practical potential and needs of interdisciplinary knowledge and competence requirements of Blockchain technology, the project activity "Development of Interdisciplinary Blockchain Skills Concept" starts with the literature review identifying the state of the art of Blockchain in Supply Chain Management and Logistics, Business and Finance, as well as Computer Science and IT-Security. The project activity further explores the academic and industry landscape of existing initiatives in education which offer Blockchain courses. Moreover, job descriptions and adverts are analyzed in order to specify today's competence requirements from enterprises. To discuss and define the future required competence, expert workshops are organized to validate the findings by academic experts. Based on the research outcome and validation, an interdisciplinary approach for Blockchain competence is developed. A second part focuses on the development of the Blockchain Best Practices activity while conducting qualitative empirical research based on case studies with industry representatives. Therefore, company interviews, based on the theoretical basis of Output 1, explore existing Blockchain use cases in different sectors. Due to the interdisciplinary importance of Blockchain technology, these skills will be defined by different perspectives of Blockchain from across multiple mentioned disciplines. The use cases and companies for the interviews will be selected based on various sampling criteria to gain results valid for a broad scale. The analysis of the various use cases will be conducted and defined in a standardized format to identify the key drivers and competence requirements for Blockchain technology applications and their adoption. On the one hand, this approach ensures comparability, on the other hand, it facilitates the development of a structured and systematic framework.Comment: arXiv admin note: text overlap with arXiv:2102.0322

    Mobility insights through consumer data: a case study of concessionary bus travel in the West Midlands

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    Current transport facilities are often built around efficiency and meeting the needs of the commuting population. These can therefore struggle to provide services suited to some of the most vulnerable members of society. In order to achieve an inclusive transport system, it is vital that transport authorities have access to detailed insights into the mobility needs and demands of different groups of the population. Increasingly, these transport authorities are making use of smart technologies and the resulting data to gain greater insight into transport users, and in turn inform decision making and policy planning. These smart technologies include automated fare collection (AFC) systems, which produce large volumes of detailed transport and mobility data from smart card transactions. To a lesser extent, retail datasets, such as loyalty card transaction data, have also been utilised. The spatiotemporal components of these data can provide valuable insight into the activity patterns of cardholders that may not be captured in traditional transport data. This thesis presents an exploration of these two forms of consumer data, with a focus on the older population in the West Midlands. Firstly, this thesis demonstrates how smart card data can be processed and analysed to provide detailed insights into the mobility patterns of concessionary bus users and how these relate to long-term changes in bus patronage recorded in the study area. Secondly, the extent to which loyalty card transaction data can be employed to understand retail behaviours and activity patterns is explored, with a focus on how these insights can be used to supplement and enhance the understanding of mobility gained from the smart card data. Finally, these insights are discussed in terms of the capacity of the current transport network to meet the mobility needs of the older population and the potential of consumer data for future transport-related research
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