Q: What is the difference between trends, insights, and state-of-the-art review article?
A trends review article, as the name suggests, describes and discusses the latest or emerging trends in the field. The trends could pertain to any aspect of the science in the field: the directions of research that are being pursued, the uses that the science is being put to, the issues that are emerging that might need to be investigated, and so on. For example, a trends review paper in artificial intelligence (AI) could look into the uses of AI in consumer behavior and e-commerce, the ethical issues arising from the entry of AI into various fields, and people’s responses to the growth of AI.
An insights review paper looks to go beyond the results and the data – to derive meaning from the data. This in turn can lead to further exploration and research. Also, there can be more than one insight discussed in such a paper; in fact, it’s a good idea to discuss multiple insights, to show that you have looked at the problem from different perspectives. An insights paper on the use of AI in e-commerce, for instance, might throw up questions such as: should AI be used more to initiate buyer interest, more to sustain interest, or more to close the purchase loop?
A state-of-the-art review paper describes the existing level of scientific development in a field. It is an assessment or evaluation of where scientific advancement has reached so far in the field. It is meant to provide more of a benchmark of the scientific progress. It may broadly indicate the level to which the science needs to go next (and therefore, may have some overlap with a trends article), but not necessarily provide any specific directions for doing so. It is also not meant to be an analysis of the level of advancement. You could do both of the above if you wish (to show in-depth knowledge of the study area), but that would make your article longer. Again, for example, a state-of-the-art review paper for AI could describe the current level of AI sophistication: AI can predict millions of possibilities, enabling it to beat humans at chess, but is at a nascent level when it comes to making complex moral decisions.