Mapping the Literature of Digital Transformation in the Context of Non-profit Organisations

Digital Transformation (DT) is a recurring theme in literature with regard to different business sectors. Among several aspects, scholars investigate organisational, technological, strategical or more distinctive traits concerning DT initiatives, such as motivation, implication or policy. However, only a few of them discuss DT initiatives focusing on the non-profit sector and the non-profit organisations (NPOs) in particular, which is the main aim of this work. This research takes over as a further step into a project intended to investigate DT initiatives in the context of NPOs. Specifically, this study comes after the development of a taxonomy identified by a systematic overview of the literature discussing DT in NPOs, afterwards used in classifying selected articles. This contribution seeks to apply some exploratory multivariate techniques performing a cluster analysis on the classification formerly pursued. To this end, we adopt the multiple correspondence analysis (MCA) and the hierarchical clustering on principal component (HCPC) methods by using some R packages. The outcome of this paper is threefold: (i) to analyse the associations between the multiple categorical variables defined by the taxonomy, (ii) to identify clouds of articles with similar discussion traits, and (iii) to group articles into clusters of similar contributions. Hence, we firstly pre-process the indicator matrix as input for the MCA. Next, we identify the principal components to reduce dimensionality. Afterwards, we adopt the Euclidean distance to find similarity among articles and Ward distance for partitioning. As a result, nine clusters recognise some recurrent patterns which would describe DT initiatives in NPOs.