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Building the capacities of civic tech communities through digital data analytics

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Peržiūrėti/Atidaryti
Maciuliene, Skarzauskiene (2020) Journal of Innovation & Knowledge.pdf (825.0Kb)
Data
2020
Autorius
Mačiulienė, Monika
Skaržauskienė, Aelita
Metaduomenys
Rodyti detalų aprašą
Santrauka
A wide range of public and private organizations, businesses and individuals throughout the world are experimenting with web-based, GIS, virtual and mobile technologies, often in collaboration with each other in order to develop civic technologies. Online communities form the basis for civic platforms, which are incubators for new ideas through peer-to-peer networks, stakeholder mobilization and collaborative and partnership engagement. Digital data analytics offers unprecedented opportunities to build capacity within communities simply because online platforms serve as acquisition hubs of structured and unstructured data. Notwithstanding, technology powered forms of engagement face multiple design and management challenges. Currently, limited research is being conducted into the online community using digital data analytics in non-business contexts. This explorative study further develops existing knowledge on civic tech communities and the use of digital data analytics. To this end, we review the previous research in order to understand how to aggregate literature on online communities, civic technologies and data analytics into a conceptual model that is useable by both academics and practitioners. The framework proposed serves as the first step in differentiating the building blocks of relevant digital data in managing civic technology communities and should be regarded as an effort to structure the available sources. Thus, the focus of the proposed conceptual model is not to offer prescriptive guidelines on the use of digital analytics, but rather to present a broader understanding of the emerging phenomenon and dimensions of data analysis.
Paskelbimo data (metai)
2020
URI
https://etalpykla.vilniustech.lt/handle/123456789/150987
Kolekcijos
  • Straipsniai Web of Science ir/ar Scopus referuojamuose leidiniuose / Articles in Web of Science and/or Scopus indexed sources [7946]

 

 

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