From Barriers to Digital Transformation Pathways in Brazil and Germany

Abstract

Digital transformation (DT) has become a strategic imperative for sustaining competitiveness in global supply chains. This study situates DT within the frameworks of Dynamic Capabilities Theory (DCT) and Structural Contingency Theory (SCT) to explain how leadership, culture, and institutional contexts shape adoption pathways in Brazil and Germany. Using a sequential mixed-methods approach, it combines a tertiary literature review with expert elicitation and Interpretive Structural Modelling (ISM), supported by DEMATEL and MICMAC analyses, to uncover hierarchical relationships among barriers and foundational technologies—Big Data Analytics (BDA), the Internet of Things (IoT), and cloud computing. The results reveal distinct causal structures: in Germany, workforce deficits and economic-risk perceptions act as root barriers that constrain managerial and cultural adaptation; in Brazil, executive sponsorship drives workforce capability and analytics development, activating subsequent IoT and cloud adoption. Across both contexts, BDA consistently emerges as the foundational enabler, indicating a layered sequence of capability accumulation. The findings demonstrate that effective digital transformation depends on leadership-enabled alignment between organisational structure and environmental contingencies. This study contributes a comparative framework linking DCT’s dynamic routines with SCT’s structural fit, providing theoretical, methodological, and policy insights for context-sensitive digitalisation strategies.