Industry 4.0 Technologies in The Service Sector: A Systematic Literature Review

Purpose – This study systematically reviews the literature on Industry 4.0 technology (I4T) adoption within the service sector—including Big Data analytics, Artificial Intelligence, and Robotics—to identify critical adoption trends, benefits, and challenges. Given the unique intangibility and heterogeneity of services, the research aims to outline a sector-specific roadmap for technological integration.
Design/methodology/approach – Following a dual-method approach, the study first employs bibliometric analysis to map the intellectual landscape of Industry 4.0 in services. This is followed by a Systematic Literature Review (SLR) of 49 empirical studies published between 2013 and 2023, indexed in major databases such as Scopus and Web of Science. Findings – The analysis reveals a distinct phased adoption model in which “Base Technologies” (e.g., Cloud Computing and Big Data) serve as a prerequisite infrastructure for “Front-end Technologies” (e.g., Robotics and AI). While I4T significantly enhances operational and financial performance, its success is heavily moderated by human-centered factors. These include customer psychological acceptance of automated interactions, and employee digital literacy. The results suggest that service-sector adoption is less about technical capability and more about balancing technological readiness with human-centric integration. Originality/value – This study extends established frameworks, specifically the Diffusion of Innovation (DOI) and the Technology-Organization-Environment (TOE) model, by integrating a human-centric dimension essential for service environments. It provides a theoretical perspective on the socio-technical barriers to digital transformation and highlights how the documented phased progression in literature reflects the maturation and increasing commercial availability of front-end technologies.