Context–Mechanism–Outcome (CMO) configurations of Digitalization in Rural Contexts: A Comparative Dataset of 35 Studies

This dataset contains a structured collection of Context–Mechanism–Outcome (CMO) configurations extracted from 35 empirical studies examining the impacts of digitalization in rural settings. The dataset is designed to support realist-informed analysis by identifying how specific contextual conditions interact with digitization processes to produce varied outcomes. The dataset was developed using a realist-informed analytical framework based on the Context–Mechanism–Outcome (CMO) heuristic (Pawson & Tilley, 1997). A qualitative content analysis was conducted on the selected studies. In particular, for each study: Relevant sections were reviewed CMOs were manually extracted and coded Categories for contexts, mechanisms, and outcomes were standardized across cases Each study has been systematically coded to identify: Contexts (C) include geographic dimension (represented by remoteness), socio-economic dimension (social vulnerability), demographic dimension (digital literacy), cultural dimension (norms and traditions), and institutional dimension (organizational capabilities, local policies). Mechanisms (M) include accessibility (e.g. to a number of services), knowledge creation and knowledge dissemination, human connection (intended as interpersonal relationship) and restructuting infrastractures, particulirly digital infrastructures. Outcomes (O) were classified as positive (access to economic resources, access to education/healthcare, strengthned social inclusion), negative (exacerbated inequalities, increased dependency), or unintended (mainly due to trust issues), and ranked by relevance based on their prominence in the study findings.