Using GenAI as co-author for teaching supply chain management in higher education

Abstract

This chapter analyzes the utility of GenAI as a means of adequately gathering information on prevalent concepts in teaching supply chain management in higher education. We first develop and portray a framework for setting up a compendium of definitions using the explanatory power of GenAI as well as the comprehensiveness of classical textbooks, accompanied and critically reviewed by supply chain management experts. We then evaluate the resulting output by reflecting the need for content- and language adaptations and the extent of expert adaptations necessary to achieve correct explanations of supply chain management concepts such that students can use them for building up a profound and correct basic vocabulary in this field. Our results identify the extent to which GenAI outputs are correct, and confirm that this equates to the degree found in studies within other disciplines (e.g., medicine). We also show that GenAI can be used for creating uniform explanations of concepts in supply chain management, but that expert knowledge is required to validate the correctness of the outputs. The framework we developed can help to utilize the different sources of information in supply chain management education appropriately.