Manual exploratory literature reviews should be a thing of the past, as technology and development of machine learning methods have matured. The learning curve for using machine learning methods is rapidly declining, enabling new possibilities for all researchers. A framework is presented on how to use topic modelling on a large collection of papers for an exploratory literature review and how that can be used for a full literature review. The aim of the paper is to enable the use of topic modelling for researchers by presenting a step-by-step framework on a case and sharing a code template. The framework consists of three steps; pre-processing, topic modelling, and post-processing, where the topic model Latent Dirichlet Allocation is used. The framework enables huge amounts of papers to be reviewed in a transparent, reliable, faster, and reproducible way.

Purpose – The purpose of this paper is to frame next-generation enterprise systems (ES). Design/methodology/approach – The model is based on a retrospective analysis of the evolution of enterprise systems, enterprise resource planning (ERP) research and emerging business requirements. Findings – The paper proposes a conceptual framework for extended enterprise resource planning (ERP II). The aim of this model is to compile present ES concepts into a comprehensive outline of ERP II, thus composing a generic map and taxonomy for corporate-wide enterprise systems. Research limitations/implications – The paper concludes that the ERP research needs to broaden its perspective in order to accommodate itself to the new issues of next-generation enterprise systems. Practical implications – The model is seen as a first step towards a tool to analyse and design complex enterprise systems architecture. Originality/value – This paper is the first attempt to formalize and capture the ERP II concept and the next-generation enterprise systems.