The rapid development of technologies has led to their increasing presence in all fields of science and in all segments of society. As a result, the emergence of Digital Transformation (DT) can be found in virtually all areas, regardless of the sector (education, banking, public administration, manufacturing, etc.), one could say that DT is "ubiquitous". This ubiquity is on the one hand understandable and expected from a technological and user point of view, but on the other hand it makes it difficult for researchers to approach the phenomenon in a holistic way, which is reflected in the limited number of taxonomies that try to capture the DT of a domain, e.g. public or local administration, in a holistic way.
The aim of the thesis is to develop a taxonomic model that defines the domains of DT in the local community (LC) in a comprehensible and holistic way, provides insight into the structure of DT itself and thus facilitates the understanding of the opportunities that DT offers, and serves as a guide for LCs on what to look out for in the DT journey. The empirical part of the thesis takes a holistic approach to the phenomenon of DT in LCs and develops a taxonomic model of DT in LCs, which presents in a comprehensible way all the domains of DT in LCs and the dimensions through which the elements of each domain pass in the DT process. For the first time in the Slovenian context, the ETDP method (Extended Taxonomy Development Procedure) is used to develop a taxonomic model of the whole DT in LC. Subsequently, a structured digital maturity (DM) model is developed based on the previously developed taxonomic model, which is used as an element for evaluating the maturity of DT in the LC and for comparing the maturity of DT in the other LCs. The results show that the majority of Slovenian LCs reach a high level of DM.
As the impact of the size of the LCs by population on the level of the DM is still debated in the literature, the possible dependence of the DM of the LC size by its actual population and by population size classes is further investigated. In both cases, the result of the correlation test showed statistical significance, which means that it can be argued that a correlation exists and that the size of the LC by population has an impact on its DM. A latent profile analysis (LPA) is also performed to find hidden subgroups of LCs or profiles with certain common characteristics in the observed data, in order to determine whether the results of the LPA analysis correlate with the demographic information on the size of LC by population. The results show that two of the four hidden LCs profiles identified correlate with size by population. The study contributes
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to a holistic understanding of the phenomenon of DT at the local level and extends the practical application of the taxonomic model developed.
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