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Browsing by Subject "data economy"

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  • Linna, Jutta (2024)
    Datafication, the continually expanding technological trend to convert different aspects of people’s lives in computable form and commodifying them, has proven to be economically significant in the last few decades. The trend has been accompanied by increasing social criticism regarding its underlying practices and ideologies, and cooperative models have been proposed as alternatives to combat issues originating from the operating models of profit-seeking data-driven companies. The thesis discusses datafication through the case of the Finnish network of cooperatives, S Group, and inspects how it frames datafication in relation to its collectively and ideologically managed business model and its customer-owners. As the owners of the cooperative are also targets of its data-based manipulations, the relationship between them is intricate and sometimes contradictory. The theoretical framework of the thesis considers the power imbalances and information asymmetries concerning the subjects and objects of data. It is divided to three perspectives: Collective perspective of cooperative action, individual perspective of consumer agency, and the relationship perspective intersecting the former two through the manipulation of decision-making environments (nudging). All three perspectives are discussed first by their original definitions, followed by discussion relating to the effects of datafication on them. The research problem in the thesis is how the aggregation of individuals purchase data into instruments of collective action is presented in the context of cooperative trade. It is researched with an interpretative grounded theory approach of collecting and analysing the research material. The material was compiled from public informational communications articles, especially press releases, news articles, and blogs collected from S Group's websites. Three interdependent levels at which human behaviour and social activity is managed are identified in the thesis: Individual level, community owners’ level, and national population level. S Group justifies these levels by their connection to each other and by assigning benefits related to the cooperatives operating principles, ideology, and practical operations to each level. Framing these benefits is additionally strengthened by the strategies of nudging and enabling used to optimistically promote datafication and consenting to it further. The results of the thesis cannot be generalized nor was this the aim of it. Instead, the thesis’ purpose is to bridge the gap between individual and collective considerations in relation to datafication. Additionally, its aim is to encourage discussion of the fair prerequisites of datafication, one of them being real possibilities of participation for individual consumers as the producers and object of data.
  • Djakonoff, Vera (2023)
    Datafication penetrates all levels of society. In order to harness public value from an expanding pool of private-produced data, there has been growing interest in facilitating business-to-government (B2G) data-sharing. This research examines the development of B2G data-sharing within the data ecosystem of the City of Helsinki. The research has identified expectations ecosystem actors have for B2G data-sharing and factors that influence the city’s ability to unlock public value from private-produced data. The research context is smart cities, with a specific focus on the City of Helsinki. Smart cities are in an advantageous position to develop novel public-private collaborations. Helsinki, on the international stage, stands out as a pioneer in the realm of data-driven smart city development. For this research, nine data ecosystem actors representing the city and companies participated in semi-structured thematic interviews through which their perceptions and experiences were mapped. The theoretical framework of this research draws from the public value management (PVM) approach in examining the smart city data ecosystem and alignment of diverse interests for a shared purpose. Additionally, the research transcends the examination of the interests in isolation and looks at how technological artefacts shape the social context and interests surrounding them. Here, the focus is on the properties of data as an artefact with anti-rival value-generation potential. The findings of this research reveal that while ecosystem actors recognise that more value can be drawn from data through collaboration, this is not apparent at the level of individual initiatives and transactions. This research shows that the city’s commitment to and facilitation of a long-term shared sense of direction and purpose among ecosystem actors is central to developing B2G data-sharing for public value outcomes. Here, participatory experimentation is key, promoting an understanding of the value of data and rendering visible the diverse motivations and concerns of ecosystem actors, enabling learning for wise, data-driven development.