Understanding STI and SDG with artificial intelligence: A review and research agenda for entrepreneurial action

Abstract

In 2015 the United Nations (UN) presented the sustainable development goals (SDGs). Since then, numerous investigations have addressed this topic. Although there is much research on the SDGs and the relationship between the SDGs and technological advances, there is little research regarding the implementation of technology for sustainable entrepreneurship, how these techniques are developed across industries, and how they can improve the global sustainability of other companies to support the 2030 sustainable agenda. Therefore, this study aims to develop a research agenda for entrepreneurial action, identifying key aspects related to science, technology, and innovation (STI) and the SDGs, and exploring how both concepts are interconnected. To this end, we conducted a systematic literature review (SLR) of 25,739 papers with machine learning and artificial intelligence techniques. Using the methodological approach of corpus linguistics (CL) and Topic Modeling with Latent Dirichlet Allocation (LDA) algorithm, we extracted keywords, topics, and frequency. The results revealed that (i) there is a research agenda for STI and the SDGs containing 28 topics grouped in three categories: “SDG,” “production business models,” and “partnership and sustainable management models”; (ii) salient topics are “responsible consumption,” “industrial action,” and “sustainable industries”; and (iii) innovation intersects all the topics.