ABSTRACT
Since they started to recognise the potential to cut costs, boost productivity, and achieve greater levels of quality, many firms have been adjusting their operations to a process-centered vision and promoting the continuous improvement mindset. To meet these business objectives, the use of natural language processing (NLP) techniques to create process models from unstructured text has become a viable alternative. The time spent by process designers and analysts during the process elicitation phase can be cut down thanks to NLP technologies, which also lower the process’s expenses for the business. The ability of NLP to automatically analyse and comprehend human language is gaining traction in engineering and management studies. It is widely used in the field of management research, but neither its analytical capabilities nor the literature surrounding those capabilities have been well explored. We analyse articles from Scopus-listed journals that use NLP as their primary analytic method to demonstrate how textual data may be used to generate management ideas in a variety of settings. We talk about how to use NLP as an analytical tool, what tools are available, what needs to be done, and what advantages and disadvantages there are. In doing so, we hope to impact future research by bringing attention to the technological and managerial difficulties of utilising NLP in the field of management.
