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.