Mathematical Model of Analysis and Optimal Harmonisation of Data for Preparation of Broadband Infrastructure Development Project in the Republic of Croatia: Contribution to Achieving Objectives of the Digital Agenda for Europe

Matej Požarnik, Tea Taras, Aleš Kranjec, Lea Robič Mohar

Abstract


Next Generation Access projects of developing broadband infrastructure, co-financed by the EU, require preparation and implementation of complex preparatory actions that are crucial for their successful implementation. Their implementation within member states contributes directly to achieving goals, defined in the Digital agenda for Europe. Preparation work on projects requires complex analyses and processing of governmental data on potential users of the new network. A mathematical model was developed within this study. Also, the Optimal Data Harmonization algorithm was developed, which incorporates the pointed mathematical model. Large amounts of projects’ input data were also processed with the Optimal Data Harmonization algorithm. Research showed that data processing without Optimal Data Harmonization algorithm is the key reason for inadequate preparation of the project because of imprecise definition of numbers and geolocations of potential users. Without applying such model, projects don’t achieve the target coverage of broadband infrastructure of the next generation access and therefore don’t contribute to the Digital agenda for Europe goals. Processing data with Optimal Data Harmonization algorithm, which is a beyond the state-of-the-art model, ensures a high-level harmonisation of national data. With these results, one can provide optimal coverage of eligible potential beneficiaries in the project. Projects in which data were processed with the Optimal Data Harmonization algorithm contribute to reaching the Digital agenda for Europe goals. The study also recommends the establishment of national central database of geolocations of the potential beneficiaries, as it would standardize the input data in all future projects.


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DOI: https://doi.org/10.11114/bms.v2i3.1823

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Business and Management Studies     ISSN 2374-5916 (Print)     ISSN 2374-5924 (Online)

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