Does digital transformation matter to improve sugarcane agroindustry? Techniques, challenges and future trends

Purpose This study aims to provide a comprehensive understanding of digital transformation in the sugarcane agroindustry. It critically synthesizes technological, contextual and methodological developments to identify research gaps and proposes a structured agenda to support sustainable and inclusive industrial transformation. Design/methodology/approach A mixed bibliometric–systematic review approach was conducted using 94 peer-reviewed articles published between 2020 and 2026, retrieved from Scopus and Web of Science. The PRISMA 2020 protocol was applied to ensure transparency and replicability. Bibliometric mapping of 461 unique records was integrated with systematic content analysis and structured through the theory–context–method (TCM) and antecedents–decisions–outcomes (ADO) integrated framework to derive a comprehensive conceptual synthesis. Findings The review reveals that digital transformation research in the sugarcane sector is dominated by upstream technological applications such as machine learning, deep learning and remote sensing but remains constrained by infrastructural, organizational and human-capacity limitations. The integrated TCM–ADO mapping uncovers critical gaps in theoretical coherence, contextual diversity and methodological balance, emphasizing the need for adaptive and socio-technical approaches to digital adoption. Practical implications The findings offer a strategic reference for researchers, practitioners and policymakers to improve data interoperability, strengthen digital literacy and promote adaptive decision-support systems that enhance operational resilience and sustainability. Originality/value This study provides the first comprehensive review of digital transformation in the sugarcane agroindustry. Unlike previous research that remains fragmented or focused on other crops, it integrates bibliometric, systematic approaches and TCM-ADO to identify key technologies, barriers and future research agenda.