Six problem formulations exist in multi-criteria decision analysis (MCDA): choice, sorting, ranking, description, elimination and design problems. MCDA methods are generally developed for choice or ranking problems. Recently, several methods have been adapted for sorting problems. However, they all assume that the criteria are independent, which is often not the case practically in real life. Therefore, this paper proposes a new sorting technique ANPSort, which can handle problems and challenges with interdependent criteria. Moreover, another practical limitation of ANP is that a high number of alternatives imply a large number of comparisons. In comparison, our proposed ANPSort requires far-less comparisons than ANP, which facilitates decision-making within large-scale problems. It further allows a structured, transparent and consistent evaluation integrating qualitative and quantitative criteria. In this paper, we contextualise and problematise this challenge and contribute through the lens of a practical case study in a higher education academic set-up specifically concentrating on a topical area of 'researcher classification', to illustrate our concept and approach.